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  • 251.
    Gustafsson, Agnetha
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Grétarsdóttir, Jakobina
    Sahlgrenska Universitetssjukhuset, Göteborg.
    Which collimator should be used for myocardial perfusion SPECT, HR or GP?2006Conference paper (Other academic)
  • 252.
    Gustafsson, Agnetha
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Jacobsson, Lars
    University of Göteborg, Sahlgrenska University Hospital.
    Johansson, Åke
    University of Göteborg, Sahlgrenska University Hospital.
    Moonen, Michaela
    University of Göteborg, Sahlgrenska University Hospital.
    Tylén, Ulf
    University of Göteborg.
    Bake, Björn
    University of Göteborg, Sahlgrenska University Hospital.
    Attenueringseffekter vid lung-SPECT av friska försökspersoner1999Conference paper (Other academic)
  • 253.
    Gustafsson, Agnetha
    et al.
    Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Karlsson, Henrik
    Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Lindblom, Gunnar
    Östergötlands Läns Landsting, Centre for Diagnostics, Department of Radiology in Linköping.
    Dosering vid helkroppscan av skelettskintigrafi2006Conference paper (Other academic)
  • 254.
    Gustafsson, Agnetha
    et al.
    Linköping University, Department of Medical and Health Sciences, Radiation Physics. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Centre for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics UHL.
    Ärlig, Åsa
    Göteborg University, Sahlgrenska University Hospital.
    Jacobsson, Lars
    Göteborg University, Sahlgrenska University Hospital.
    Ljungberg, Michael
    Lund University.
    Wikkelsö, Carsten
    Göteborg University, Sahlgrenska University Hospital.
    Comptonbaserad spridningskorrektion och energifönsterinställning vid CBF SPECT: En Monte Carlo studie2000Conference paper (Other academic)
  • 255.
    Gustafsson, Agnetha
    et al.
    Department of Radiation Physics, Göteborg University, Sahlgrenska University Hospital, Göteborg, Sweden .
    Ärlig, Åsa
    Department of Radiation Physics, Göteborg University, Sahlgrenska University Hospital, Göteborg, Sweden .
    Jacobsson, Lars
    Department of Radiation Physics, Göteborg University, Sahlgrenska University Hospital, Göteborg, Sweden .
    Ljungberg, Michael
    Radiation Physics Department, Lund University, The Jubileum Institute, Lund, Sweden .
    Wikkelsö, Carsten
    Institute of Clinical Neuroscience, Göteborg University, Sahlgrenska University Hospital, Göteborg, Sweden .
    Dual-window scatter correction and energy window setting in cerebral blood flow SPECT: a Monte Carlo study2000In: Physics in Medicine and Biology, ISSN 0031-9155, E-ISSN 1361-6560, Vol. 45, no 11, p. 3431-3440Article in journal (Refereed)
    Abstract [en]

    The image quality in SPECT studies of the regional cerebral blood flow (rCBF) performed with 99mTc-HMPAO is degraded by scattered photons. The finite energy resolution of the gamma camera makes the detection of scattered photons unavoidable, and this is observed in the image as an impaired contrast between grey and white matter structures.

    In this work, a Monte Carlo simulated SPECT study of a realistic voxel-based brain phantom was used to evaluate the resulting contrast-to-noise ratio for a number of energy window settings, with and without the dual-window scatter correction. Values of the scaling factor k, used to obtain the fraction of scattered photons in the photopeak window, were estimated for each energy window.

    The use of a narrower, asymmetric, energy discrimination window improved the contrast, with a subsequent increase in statistical noise due to the lower number of counts. The photopeak-window setting giving the best contrast-to-noise ratio was found to be the same whether or not scatter correction was applied. Its value was 17% centred at 142 keV. At the optimum photopeak-window setting, the contrast was improved by using scatter correction, but the contrast-to-noise ratio was made worse.

  • 256.
    Gustafsson, U
    et al.
    Umeå University Hospital, Umeå, Sweden.
    Larsson, M.
    Royal Institute of Technology, Stockholm, Sweden.
    Bjällmark, Anna
    Royal Institute of Technology, Stockholm, Sweden.
    Lindqvist, P.
    Umeå University Hospital, Umeå, Sweden.
    A'roch, R.
    Umeå University Hospital, Umeå, Sweden.
    Haney, M.
    Umeå University Hospital, Umeå, Sweden.
    Waldenstrom, A.
    Umeå University Hospital, Umeå, Sweden.
    The rotation axis of the left ventricle in acute myocardial ischemia2010In: European Journal of Echocardiography, ISSN 1525-2167, E-ISSN 1532-2114, Vol. 11, no suppl_2, p. ii124-ii154, article id P908Article in journal (Refereed)
  • 257.
    Gustafsson, U
    et al.
    Umeå University Hospital, Umeå, Sweden.
    Larsson, M.
    Royal Institute of Technology, Stockholm, Sweden.
    Bjällmark, Anna
    Royal Institute of Technology, Stockholm, Sweden.
    Lindqvist, P.
    Umeå University Hospital, Umeå, Sweden.
    Brodin, L.
    Royal Institute of Technology, Stockholm, Sweden.
    Waldenstrom, A.
    Umeå University Hospital, Umeå, Sweden.
    The rotation axis of the left ventricle. A new concept in cardiac function2010In: European Journal of Echocardiography, ISSN 1525-2167, E-ISSN 1532-2114, Vol. 11, no suppl_2, p. ii45-ii75, article id P499Article in journal (Refereed)
  • 258.
    Gyllencreutz, E.
    et al.
    Karolinska Inst, Stockholm, Sweden.;Ostersund Hosp, Dept Obstet & Gynecol, Ostersund, Sweden..
    Lu, Ke
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics.
    Lindecrantz, Kaj
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics. Karolinska Inst, Stockholm, Sweden.
    Lindqvist, P.
    Karolinska Inst, Stockholm, Sweden..
    Nordström, L.
    Karolinska Inst, Stockholm, Sweden..
    Holzmann, M.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Obstet & Gynecol, Stockholm, Sweden..
    Abtahi, F.
    Karolinska Inst, Stockholm, Sweden.;Karolinska Univ Hosp, Dept Clin Physiol, Stockholm, Sweden..
    Validation of a computerised algorithm to quantify fetal heart rate deceleration area: An observational study2018In: British Journal of Obstetrics and Gynecology, ISSN 1470-0328, E-ISSN 1471-0528, Vol. 125, p. 54-54Article in journal (Other academic)
  • 259.
    Gårdhagen, Roland
    et al.
    Linköping University, Department of Mechanical Engineering. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Renner, Johan
    Linköping University, Department of Mechanical Engineering. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Karlsson, Matts
    Linköping University, Department of Biomedical Engineering. Linköping University, The Institute of Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV).
    Assessment of Geometrical Influence on WSS Estimation in the Human Aorta2006In: WSEAS Transactions on Fluid Mechanics, ISSN 1790-5087, Vol. 4, no 1, p. 318-326Article in journal (Refereed)
    Abstract [en]

    Computational fluid dynamics simulations were performed on a stenosed human aorta with poststenotic dilatation, in order to estimate wall shear stress (WSS). WSS is important due to its correlation with atherosclerosis. Both steady-state and non-stationary simulations were conducted. Three different models were created from a set of MRI images. Comparison of geometrically different models was accomplished by using geometrical landmarks and a comparison parameter. Geometrical differences had larger influence on WSS magnitude than inflow rotation in steady-state results for the models used. In non-stationary flow the largest differences in WSS are found when the flow velocity near the wall is low e.g. when the inflow is low or in recirculation regions.

  • 260.
    Hall, Håkan
    et al.
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preclinical PET Platform.
    Takahashi, Kayo
    Center for Molecular Imaging Science, Kobe, Japan.
    Erlandsson, Maria
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC.
    Estrada, Sergio
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Pharmacy, Department of Medicinal Chemistry, Preclinical PET Platform.
    Razifar, Pasha
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Bergström, Elisabeth
    Uppsala Imanet, Uppsala, Sweden.
    Långström, Bengt
    Uppsala University, Disciplinary Domain of Science and Technology, Chemistry, Department of Chemistry - BMC, Physical Organic Chemistry.
    Pharmacological characterization of 18F-labeled vorozole analogs2012In: Journal of labelled compounds & radiopharmaceuticals, ISSN 0362-4803, E-ISSN 1099-1344, Vol. 55, no 14, p. 484-490Article in journal (Refereed)
    Abstract [en]

    Two F-18-labeled analogs of vorozole ([F-18]FVOZ and [F-18]FVOO) have been developed as potential tools for the in vivo characterization of aromatase. The pharmacologicalproperties of these radioligands were evaluated using in vitro binding and in vivo distribution studies in the rat and primate. Saturation binding studies using rat ovary gave K-D and B-max values of 0.21 +/- 0.1 nM and 210 +/- 20 fmol/mg, respectively, for [F-18]FVOZ, and 7.6 +/- 1nMand 293 +/- 12fmol/mg, respectively, for [F-18]FVOO. Organ distribution studies in rats showed the highest accumulation in the adrenal glands, with standardized uptake values (SUVs) of 15 to 20, followed by ovaries and liver with SUVs of approximately 5. Ex vivo and in vitro autoradiography of the rat brain showed specific binding of both [F-18]FVOZ and [F-18]FVOO mainly in the amygdala. Positron emission tomography (PET) studies were performed in the Rhesus monkey, and these showed displaceable binding in the amygdala and the hypothalamus preoptic area. The PET images were also analyzed using masked volume-wise principal component analysis. These studies suggest that [F-18]FVOZ might be a suitable tracer for the study of aromatase in vitro and in vivo, and could be an alternative to [C-11]vorozole in human PET studies.

  • 261.
    Hamid Muhammed, Hamed
    KTH, School of Technology and Health (STH), Medical Engineering.
    Image Enhancement Combined with Reduction of X-Ray Dose During PCI-Operations2010Conference paper (Other academic)
  • 262.
    Hamid Muhammed, Hamed
    et al.
    School of Technology and Health (STH), Royal Institute of Technology (KTH), Alfred Nobels Alle 10, SE-141 52 Huddinge, Sweden.
    Azar, Jimmy C
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automatic Characterization of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences Using Spatiotemporal and Spatiospectral 2D Maps.2014In: International Journal of Biomedical Imaging, ISSN 1687-4188, E-ISSN 1687-4196, Vol. 2014, article id 876267Article in journal (Refereed)
    Abstract [en]

    A novel method for characterizing and visualizing the progression of waves along the walls of the carotid artery is presented. The new approach is noninvasive and able to simultaneously capture the spatial and the temporal propagation of wavy patterns along the walls of the carotid artery in a completely automated manner. Spatiotemporal and spatiospectral 2D maps describing these patterns (in both the spatial and the frequency domains, resp.) were generated and analyzed by visual inspection as well as automatic feature extraction and classification. Three categories of cases were considered: pathological elderly, healthy elderly, and healthy young cases. Automatic differentiation, between cases of these three categories, was achieved with a sensitivity of 97.1% and a specificity of 74.5%. Two features were proposed and computed to measure the homogeneity of the spatiospectral 2D map which presents the spectral characteristics of the carotid artery wall's wavy motion pattern which are related to the physical, mechanical (e.g., elasticity), and physiological properties and conditions along the artery. These results are promising and confirm the potential of the proposed method in providing useful information which can help in revealing the physiological condition of the cardiovascular system.

  • 263.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering, Systems Safety and Management.
    Azar, Jimmy C
    Centre for Image Analysis, Uppsala University.
    Semi-Automated Classification of the Physiological Condition of the Carotid Artery in 2D Ultrasound Image Sequences2014In: WSEAS Transactions on Biology and Biomedicine, ISSN 1109-9518, E-ISSN 2224-2902, ISSN E-ISSN 2224-2902, Vol. 11, p. 35-44Article in journal (Refereed)
    Abstract [en]

    Abstract: -A novel automated method for the classification of the physiological condition of the carotid arteryin 2D ultrasound image sequences is introduced. Unsupervised clustering was applied for the segmentationprocess in which both spatial and temporal information was utilized. Radial distension is then measured in theinner surface of the vessel wall, and this characteristic signal is extracted to reveal the detailed radial motion ofthe variable inner part of the vessel wall that is in contact with flowing blood. Characteristic differences in thistime signal were noticed among healthy young, healthy elderly and pathological elderly cases. The discreteFourier transform of the radial distension signal is then computed, and the area subtended by the transform iscalculated and utilized as a diagnostic feature. The method was tested successfully and could differentiateamong the categories of patients mentioned above. Therefore, this computer-aided method would significantlysimplify the task of medical specialists in detecting any defects in the carotid artery and thereby in detectingearly cardiovascular symptoms. The significance of the proposed method is that it is intuitive, semi-automatic,reproducible, and significantly reduces the reliance upon subjective measures.

  • 264.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Darvish, Niloufar
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Öçba, Fatma Nadide
    KTH, School of Technology and Health (STH), Health Systems Engineering.
    Bone, Dianna
    Karolinska Hospital, SE-17671 Stockholm, Sweden.
    A New Approach to the Presentation of Myocardial SPECT Images: Radial Slices—Data Reduction without Loss of Information2013In: Engineering, ISSN 1947-394X, Vol. 5, no 10BArticle in journal (Refereed)
    Abstract [en]

    Objective: SPECT data from myocardial perfusion imaging (MPI) are normally displayed as a set of three slices orthogonal to the left ventricular (LV) long axis. For data presentation, the images are orientated about the LV long axis. Therefore, radial slices provide a suitable alternative to standard orthogonal slices, with the advantage of requiring fewer slices to adequately represent the data. In this study, a semi-automatic method is developed for displaying MPI SPECT data as a set of radial slices orientated about the LV axis. The aim is to reduce the number of slices viewed without loss of information and independently from the heart size. Method: Standard short axis slices, orientated perpendicular to the LV axis, are utilized.The skeleton of the segmented myocardium is found and the true LV axis is determined in each central long slice. The LV axis of the whole volume is determined by aligning the axes of all slices. Result: Radial slices centered about this axis were generated by integration over a sector equal to the resolution of the imaging system which was of the order of 1.2 cm. Therefore, assuming a mean LV diameter of 8 cm, 20 slices were sufficient to represent a non-gated study. Gated information could be adequately displayed with 4 slices integrated over an angle of 45. Conclusion: A semi-automatic method for generating radial slices from SPECT MPI short axis slices has been developed.

  • 265.
    Hamid Muhammed, Hamed
    et al.
    KTH, School of Technology and Health (STH), Informatics, logistics and management (Closed 20130701).
    Zengin, Ziya
    Karadeniz Technical University, Trabzon, Turkey.
    Monte Carlo Simulation and a Review of the Physics of the Positron Annihilation Process in PET2013In: Engineering, ISSN 1947-394X, Vol. 5, no 10BArticle in journal (Refereed)
    Abstract [en]

     In this paper, we investigate the physics of the positron annihilation process, which occurs in a PET imaging system. In particular, the diffusion of beta particles (positrons) within water was addressed. Beta particles are emitted isotropically from the same source point with random directions and randomly chosen energy levels. After traversing a certain distance within water, beta particles lose a certain amount of its energy. The inelastic collisions with atomic electrons are mainly responsible for the energy dissipation of charged particles, such as electrons and positrons (that have low mass). The energy loss rate due to inelastic process is estimated by using the Beta-Bloch formula. These results help in understanding how to develop and implement a computationally efficient Monte Carlo Simulation of the positron annihilation process.

  • 266.
    Han, Songfeng
    et al.
    Institute of Optics, University of Rochester.
    Johansson, Johannes
    ICFO- Institut de Ciències Fotòniques.
    Mireles, Miguel
    ICFO- Institut de Ciències Fotòniques.
    Proctor, Ashley R
    Department of Biomedical Engineering, University of Rochester.
    Hoffman, Michael D
    Department of Biomedical Engineering, University of Rochester.
    Vella, Joseph B
    Department of Biomedical Engineering, University of Rochester.
    Benoit, Danielle S W
    Department of Biomedical Engineering, University of Rochester.
    Durduran, Turgut
    ICFO- Institut de Ciències Fotòniques.
    Choe, Regine
    Department of Biomedical Engineering, University of Rochester.
    Non-contact scanning diffuse correlation tomography system for three-dimensional blood flow imaging in a murine bone graft model.2015In: Biomedical Optics Express, ISSN 2156-7085, E-ISSN 2156-7085, Vol. 6, no 7Article in journal (Refereed)
    Abstract [en]

    A non-contact galvanometer-based optical scanning system for diffuse correlation tomography was developed for monitoring bone graft healing in a murine femur model. A linear image reconstruction algorithm for diffuse correlation tomography was tested using finite-element method based simulated data and experimental data from a femur or a tube suspended in a homogeneous liquid phantom. Finally, the non-contact system was utilized to monitor in vivo blood flow changes prior to and one week after bone graft transplantation within murine femurs. Localized blood flow changes were observed in three mice, demonstrating a potential for quantification of longitudinal blood flow associated with bone graft healing.

  • 267.
    Hanga, Alexander
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Optimization of image reconstruction of 123I DAT SPECT with a LEGP collimator2015Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In SPECT, diagnoses based on quantitative measurements may be uncertain due to high noise levels and low spatial resolution. 123I DAT SPECT has been shown to have a relatively high sensitivity and specificity, but improving image quality could potentially increase these values even further, especially for early cases with parkinsonian syndromes. The aim of the study was to optimise the reconstruction protocol for 123I DAT SPECT with a LEGP collimator, using a resolution recovery algorithm included in the iterative reconstruction, and compare to images reconstructed without resolution recovery. The optimization concentrated on critical frequency of the post-reconstruction Butterworth filter and the number of reconstruction iterations. Monte Carlo simulations of a morphological brain phantom with typical DAT SPECT uptake were used for this part of the study. From contrast-to-noise diagrams, it was found that a critical frequency of 0.50 cm-1 (power factor 8) was the most optimal of the studied filters. The optimal number of OSEM iterations was evaluated by a radiologist, specialized in nuclear medicine, and 8 iterations with 6 subsets were chosen. A group of 20 subjects diagnosed with Parkinson’s disease (PD) were then be compared to a group of 20 healthy controls, with respect to uptake ratios for caudate nucleus, putamen and the whole striatum (background region: whole cortex or the occipital lobe). Uptake ratios were calculated using the software Exini DAT for images reconstructed both with and without resolution recovery. It was found that the group differences were highly significant both with and without resolution recovery. However, in putamen, where early stages of PD first manifests, the group significance of uptake ratios improved from 7.2E-14 to 8.2E-15 (background: occipital lobe) or 2.4E-14 to 8.4E-16 (background: whole cortex) when using resolution recovery. A higher spatial resolution seems to be an advantage for quantitative evaluation of 123I DAT SPECT.

  • 268.
    Haufe, William
    et al.
    Department of Radiology, University of California, San Diego, San Diego, CA, United states.
    Hooker, Jonathan
    Department of Radiology, University of California, San Diego, San Diego, CA, United States.
    Schlein, Alexandra
    Department of Radiology, University of California, San Diego, San Diego, CA, United States.
    Szeverenyi, Nikolaus
    Department of Radiology, University of California, San Diego, San Diego, CA, United States.
    Borga, Magnus
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Advanced MR Analytics AB, Linköping, Sweden.
    Dahlqvist Leinhard, Olof
    Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Advanced MR Analytics AB, Linköping, Sweden.
    Romu, Thobias
    Linköping University, Department of Biomedical Engineering, Medical Informatics. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Advanced MR Analytics AB, Linköping, Sweden.
    Tunón, Patrik
    Advanced MR Analytics AB, Linköping, Sweden.
    Horgan, Santiago
    Surgery, University of California, San Diego, San Diego, CA, United States.
    Jacobsen, Garth
    Surgery, University of California, San Diego, San Diego, CA, United States.
    Schwimmer, Jeffrey B
    University of California, San Diego, San Diego, CA, United States.
    Reeder, Scott B
    University of Wisconsin, Madison, Madison, WI, United States.
    Sirlin, Claude B.
    Department of Radiology, University of California, San Diego, San Diego, CA, United States.
    Feasibility of an automated tissue segmentation technique in a longitudinal weight loss study2016Conference paper (Other academic)
    Abstract [en]

    To address the problems inherent in manual methods, a novel, semi-automated tissue segmentation image analysis technique has been developed. The purpose of this study was to demonstrate the feasibility and describe preliminary observations of applying this technique to quantify and monitor longitudinal changes in abdominal adipose tissue and thigh muscle volume in obese adults during weight loss. Abdominal adipose tissue and thigh muscle volume decreased during weight loss. As a proportion of body weight, adipose tissue volumes decreased during weight loss. By comparison, as a proportion of body weight, thigh muscle volume increased.

  • 269.
    Hauptmann, Andreas
    et al.
    UCL, Dept Comp Sci, London WC1 6BT, England..
    Lucka, Felix
    UCL, Dept Comp Sci, London WC1 6BT, England.;Ctr Wiskunde & Informat, NL-1098 XG Amsterdam, Netherlands..
    Betcke, Marta
    UCL, Dept Comp Sci, London WC1 6BT, England..
    Huynh, Nam
    Adler, Jonas
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematics (Div.). Elekta, S-10393 Stockholm, Sweden..
    Cox, Ben
    UCL, Dept Med Phys & Biomed Engn, London WC1 6BT, England..
    Beard, Paul
    UCL, Dept Med Phys & Biomed Engn, London WC1 6BT, England..
    Ourselin, Sebastien
    UCL, Dept Comp Sci, London WC1 6BT, England..
    Arridge, Simon
    UCL, Dept Comp Sci, London WC1 6BT, England..
    Model-Based Learning for Accelerated, Limited-View 3-D Photoacoustic Tomography2018In: IEEE Transactions on Medical Imaging, ISSN 0278-0062, E-ISSN 1558-254X, Vol. 37, no 6, p. 1382-1393Article in journal (Refereed)
    Abstract [en]

    Recent advances in deep learning for tomographic reconstructions have shown great potential to create accurate and high quality images with a considerable speed up. In this paper, we present a deep neural network that is specifically designed to provide high resolution 3-D images from restricted photoacoustic measurements. The network is designed to represent an iterative scheme and incorporates gradient information of the data fit to compensate for limited view artifacts. Due to the high complexity of the photoacoustic forward operator, we separate training and computation of the gradient information. A suitable prior for the desired image structures is learned as part of the training. The resulting network is trained and tested on a set of segmented vessels from lung computed tomography scans and then applied to in-vivo photoacoustic measurement data.

  • 270.
    Hedman, Angelica
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Gogani, J. Bahar
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Granström, M.
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Andersson, Jonas S.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Ramebäck, H.
    Swedish Defence Research Agency, Division of CBRN Defence and Security, SE-90182 Umeå, Sweden; Chalmers University of Technology, Department of Chemical and Biological Engineering, Nuclear Chemistry, SE-41296 Göteborg, Sweden.
    Characterization of HPGe detectors using Computed Tomography2015In: Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, ISSN 0168-9002, E-ISSN 1872-9576, Vol. 785, no 11 June 2015, p. 21-25Article in journal (Refereed)
    Abstract [en]

    Computed Tomography (CT) high resolution imaging have been used to investigate if there is a significant change in the crystal-to-window distance, i.e. the air gap thickness, in a small n-type detector cooled to 77 K, and in a medium sized p-type HPGe detector when cooled to 100 K. The findings were compared to detector dimension data made available by the manufacturer. The air gap thickness increased by (0.38 +/- 0.07) mm for the n-type detector and by (0.40 +/- 0.15) mm for the p-type detector when the detectors were cooled to 77 resp. 100 K compared to at room temperature. Monte Carlo calculations indicate that these differences have a significant impact on the efficiency in close geometries (< 5 cm). In the energy range of 40-700 keV with a source placed directly on endcap, the change in detector efficiency with temperature is 1.9-2.9% for the n-type detector and 0.3-2.1% for the p-type detector. The measured air gap thickness when cooling the detector was 1.1 mm thicker than manufacturer data for the n-type detector and 0.2 mm thicker for the p-type detector. In the energy range of 40-700 keV and with a source on endcap, this result in a change in detector efficiency of 5.2-7.1% for the n-type detector and 0.2-1.0% for the p-type detector, Le the detector efficiency is overestimated using data available by the manufacturer. (C) 2015 Elsevier B.V. All rights reserved.

  • 271. Hellier, David
    et al.
    Samur, Evren
    Passenger, Josh
    Spälter, Ulrich
    Frimmel, Hans
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis.
    Appleyard, Mark
    Bleuler, Hannes
    Ourselin, Sébastien
    A modular simulation framework for colonoscopy using a new haptic device2008In: Medicine Meets Virtual Reality 16, Amsterdam, The Netherlands: IOS Press , 2008, p. 165-170Conference paper (Refereed)
  • 272.
    Herterich, Rebecka
    et al.
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems.
    Sumarokova, Anna
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems.
    Coil Sensitivity Estimation and Intensity Normalisation for Magnetic Resonance Imaging2019Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The quest for improved efficiency in magnetic resonance imaging has motivated the development of strategies like parallel imaging where arrays of multiple receiver coils are operated simultaneously in parallel. The objective of this project was to find an estimation of phased-array coil sensitivity profiles of magnetic resonance images of the human body. These sensitivity maps can then be used to perform an intensity inhomogeneity correction of the images. Through investigative work in Matlab, a script was developed that uses data embedded in raw data from a magnetic resonance scan, to generate coil sensitivities for each voxel of the volume of interest and recalculate them to two-dimensional sensitivity maps of the corresponding diagnostic images. The resulting mapped sensitivity profiles can be used in Sensitivity Encoding where a more exact solution can be obtained using the carefully estimated sensitivity maps of the images.

  • 273.
    Hildeman, Anders
    et al.
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Bolin, David
    Department of Mathematical Sciences, Chalmers University of Technology, Sweden.
    Wallin, Jonas
    Department of Statistics, Lund University.
    Johansson, Adam
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Nyholm, Tufve
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Asklund, Thomas
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Oncology.
    Yu, Jun
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Hildeman, A., Bolin, D., Wallin, J., Johansson, A., Nyholm, T., Asklund, T., and Yu, J. Whole-brain substitute CT generation using Markov random field mixture models.2016Manuscript (preprint) (Other academic)
    Abstract [en]

    Computed tomography (CT) equivalent information is needed for attenuation correction in PET imaging and for dose planning in radiotherapy. Prior work has shown that Gaussian mixture models can be used to generate a substitute CT (s-CT) image from a specific set of MRI modalities. This work introduces a more flexible class of mixture models for s-CT generation, that incorporates spatial dependency in the data through a Markov random field prior on the latent field of class memberships associated with a mixture model. Furthermore, the mixture distributions are extended from Gaussian to normal inverse Gaussian (NIG), allowing heavier tails and skewness. The amount of data needed to train a model for s-CT generation is of the order of 10^8 voxels. The computational efficiency of the parameter estimationand prediction methods are hence paramount, especially when spatial dependency is included in the models. A stochastic Expectation Maximization (EM) gradient algorithm is proposed in order to tackle this challenge. The advantages of the spatial model and NIG distributions are evaluated with a cross-validation study based ondata from 14 patients. The study show that the proposed model enhances the predictive quality of the s-CT images by reducing the mean absolute error with 17.9%. Also, the distribution of CT values conditioned on the MR images are better explainedby the proposed model as evaluated using continuous ranked probability scores.

  • 274.
    Hoefener, Henning
    et al.
    Fraunhofer MEVIS, Germany.
    Homeyer, Andre
    Fraunhofer MEVIS, Germany.
    Weiss, Nick
    Fraunhofer MEVIS, Germany.
    Molin, Jesper
    Sectra AB, Teknikringen 20, S-58330 Linkoping, Sweden.
    Lundström, Claes
    Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Sectra AB, Teknikringen 20, S-58330 Linkoping, Sweden.
    Hahn, Horst K.
    Fraunhofer MEVIS, Germany; Jacobs Univ, Germany.
    Deep learning nuclei detection: A simple approach can deliver state-of-the-art results2018In: Computerized Medical Imaging and Graphics, ISSN 0895-6111, E-ISSN 1879-0771, Vol. 70, p. 43-52Article in journal (Refereed)
    Abstract [en]

    Background: Deep convolutional neural networks have become a widespread tool for the detection of nuclei in histopathology images. Many implementations share a basic approach that includes generation of an intermediate map indicating the presence of a nucleus center, which we refer to as PMap. Nevertheless, these implementations often still differ in several parameters, resulting in different detection qualities. Methods: We identified several essential parameters and configured the basic PMap approach using combinations of them. We thoroughly evaluated and compared various configurations on multiple datasets with respect to detection quality, efficiency and training effort. Results: Post-processing of the PMap was found to have the largest impact on detection quality. Also, two different network architectures were identified that improve either detection quality or runtime performance. The best-performing configuration yields f1-measures of 0.816 on Hamp;E stained images of colorectal adenocarcinomas and 0.819 on Ki-67 stained images of breast tumor tissue. On average, it was fully trained in less than 15,000 iterations and processed 4.15 megapixels per second at prediction time. Conclusions: The basic PMap approach is greatly affected by certain parameters. Our evaluation provides guidance on their impact and best settings. When configured properly, this simple and efficient approach can yield equal detection quality as more complex and time-consuming state-of-the-art approaches. (C) 2018 The Authors. Published by Elsevier Ltd.

  • 275.
    Holmberg, August
    Umeå University, Faculty of Science and Technology, Department of Physics.
    Investigation of Attenuation Corrections for External Hardware in PET/MR Imaging2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
  • 276.
    Holmberg, Daniel
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Optimisation of image acquisition and reconstruction of 111In-pentetrotide SPECT2012Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The aim of this study is to optimise the acquisition and reconstruction for SPECT with 111In- pentetrotide with the iterative reconstruction software OSEMS. For 111In-pentetrotide SPECT, the uptake in the tumour is usually high compared to uptake in normal tissue. It may, however, be difficult to detect small tumours with the SPECT method because of high noise levels and the low spatial resolution. The liver is a common region for somatostatin-positive metastases, and to visually detect small tumours in the liver, as early as possible, is important for an effective treatment of the cancer disease.

    The study concentrates on the acquired number of projections, the subset size in the OSEM reconstruction and evaluates contrast as a function of noise for a range of OSEM iterations. The raw-data projections are produced using Monte Carlo simulations of an anthropomorphic phantom, including tumours in the liver. Two General Electric (GE) collimators are evaluated, the extended low-energy general-purpose (ELEGP) and the medium energy general-purpose (MEGP) collimator. Three main areas of reconstruction are investigated. First the reconstructions are performed for so called full time scans with the acquisition time used clinically. Also the effect of performing the examination in half-time or with half the injected activity is evaluated with the most optimal settings gained from the full time scans for both collimators. In addition images reconstructed without model-based compensation are also included for comparison.

    This study is a continuation of a previous study on 111In-pentetrotide SPECT where collimator choice and model-based compensation were evaluated for a cylindrical phantom representing small tumours in liver background. As in the previous study, ELEGP proved to be the better collimator. For ELEGP, the most optimal setting was 30 projection angles and a subset size of 6 projections in the OSEM reconstruction, and for MEGP optimal setting was 60 projections and 4 subsets. The difference between the different collimator settings were, however, rather small but proven significant. For both collimators the half-time scan including model-based compensation was better compared to the full-time reconstructions without model-based compensation.

  • 277. Holzwarth, Karolin
    et al.
    Köhler, Ralf
    Philipsen, Lars
    Tokoyoda, Koji
    Ladyhina, Valeriia
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Niesner, Raluca A.
    Hauser, Anja E.
    Multiplexed fluorescence microscopy reveals heterogeneity among stromal cells in mouse bone marrow sections2018In: Cytometry Part A, ISSN 1552-4922, E-ISSN 1552-4930, Vol. 93, no 9, p. 876-888Article in journal (Refereed)
  • 278. Honarvar, H.
    et al.
    Strand, J.
    Perols, Anna
    KTH, School of Biotechnology (BIO), Protein Technology.
    Orlova, Anna
    Selvaraju, R. K.
    Eriksson Karlström, Amelie
    KTH, School of Biotechnology (BIO), Protein Technology.
    Tolmachev, V.
    Position for site-specific attachment of a DOTA chelator to synthetic affibody molecules has a different influence on the targeting properties of 68Ga-Compared to 111in-labeled conjugates2014In: Molecular Imaging, ISSN 1535-3508, E-ISSN 1536-0121, Vol. 13, no 10Article in journal (Refereed)
    Abstract [en]

    Affibody molecules, small (7 kDa) scaffold proteins, are a promising class of probes for radionuclide molecular imaging. Radiolabeling of Affibody molecules with the positron-emitting nuclide 68Ga would permit the use of positron emission tomography (PET), providing better resolution, sensitivity, and quantification accuracy than single-photon emission computed tomography (SPECT). The synthetic anti-HER2 ZHER2:S1 Affibody molecule was conjugated with DOTA at the N-terminus, in the middle of helix 3, or at the Cterminus. The biodistribution of 68Ga-and 111In-labeled Affibody molecules was directly compared in NMRI nu/nu mice bearing SKOV3 xenografts. The position of the chelator strongly influenced the biodistribution of the tracers, and the influence was more pronounced for 68Ga-labeled Affibody molecules than for the 111In-labeled counterparts. The best 68Ga-labeled variant was 68Ga-[DOTA-A1]-ZHER2:S1, which provided a tumor uptake of 13 ± 1 %ID/g and a tumor to blood ratio of 39 ± 12 at 2 hours after injection. 111In-[DOTA-A1]-ZHER2:S1 and 111In-[DOTA-K58]-ZHER2:S1 were equally good at this time point, providing a tumor uptake of 15 to 16 %ID/g and a tumor to blood ratio in the range of 60 to 80. In conclusion, the selection of the best position for a chelator in Affibody molecules can be used for optimization of their imaging properties. This may be important for the development of Affibody-based and other protein-based imaging probes.

  • 279.
    Hope, Michael D.
    et al.
    University of California, San Francisco, USA.
    Dyverfeldt, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. Östergötlands Läns Landsting, Heart and Medicine Center, Department of Clinical Physiology in Linköping. University of California, San Francisco, USA.
    Thoracic Aorta Disease: Flow Evaluation by MR2013In: MRI and CT of the Cardiovascular System / [ed] Charles B Higgins; Albert de Roos, Philadelphia, PA: Lippincott Williams & Wilkins, 2013, 3, p. -676Chapter in book (Other academic)
    Abstract [en]

    Leave no disease undetected with MRI and CT of the Cardiovascular System, your definitive guide to magnetic resonance and computed tomography for cardiovascular health. Authored by a collaboration of international experts, this vivid, four-color third edition imparts the latest technologies in a rapidly advancing field. With topics that range from anatomy, to MR in infants and children, to risk assessment in ischemic heart disease  this text includes seven new chapters to reflect the rising tide of technological discovery as it pertains to cardiology.  Thanks to its expert analysis, procedural guide to implementation, and profound understanding of the recent advances in cardiovascular imagining, MRI and CT of the Cardiovascular System gives you all the tools necessary for powerful screening, diagnosis, and  cardiovascular care. Features:

    --New chapters reflecting  technological discoveries in cardiology  --Color illustrations for heightened clarity --Companion website with fully searchable text --Units organized by pathology and disease detection --Fully updated information on application of MR and CT--Up-to-date analysis of emerging multi-detector CT

  • 280.
    Hope, Michael D.
    et al.
    University of California, San Francisco, USA.
    Dyverfeldt, Petter
    University of California, San Francisco, USA.
    Acevedo-Bolton, Gabriel
    University of California, San Francisco, USA.
    Wrenn, Jarrett
    University of California, San Francisco, USA.
    Foster, Elyse
    University of California, San Francisco, USA.
    Tseng, Elaine
    University of California, San Francisco, USA.
    Saloner, David
    University of California, San Francisco, USA.
    Post-stenotic dilation: evaluation of ascending aortic dilation with 4D flow MR imaging2012In: International Journal of Cardiology, ISSN 0167-5273, E-ISSN 1874-1754, Vol. 156, no 2, p. e40-e42Article in journal (Other academic)
  • 281.
    Hope, Michael D.
    et al.
    University of California, San Francisco, USA.
    Sedlic, Tony
    University of California, San Francisco, USA.
    Dyverfeldt, Petter
    Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, Department of Medical and Health Sciences, Division of Cardiovascular Medicine. Linköping University, Faculty of Health Sciences. University of California, San Francisco, USA.
    Cardiothoracic Magnetic Resonance Flow Imaging2013In: Journal of thoracic imaging, ISSN 0883-5993, E-ISSN 1536-0237, Vol. 28, no 4, p. 217-230Article in journal (Refereed)
    Abstract [en]

    Multidimensional blood flow imaging with magnetic resonance has rapidly evolved over the last decade. The technique, often referred to as 4-dimensional (4D) flow, can now reliably image the heart and principal vessels of the chest in ≤15 minutes. In addition to dynamic 3D flow visualization, a range of unique quantitative hemodynamic markers can be calculated from 4D flow data. In this review article, we describe some of the more promising of these hemodynamic markers, including pulse wave velocity, pressure, turbulent kinetic energy, wall shear stress, and flow eccentricity. Evaluation of a range of cardiothoracic disorders has been explored with 4D flow, and many applications have been proposed. We also review the potential clinical applications of 4D flow in 4 broad contexts: the aorta, the pulmonary artery, acquired heart disease, and complex congenital heart disease. Promising preliminary results will be highlighted, including the use of abnormal systolic blood flow to risk-stratify patients for progressive valve-related aortic disease, turbulent kinetic energy to directly assess the hemodynamic impact of a stenotic lesion, and altered intracardiac flow to identify early heart failure. We discuss ongoing research efforts in the context of the larger clinical goals of 4D flow: the use of unique hemodynamic markers to (1) identify cardiovascular disease processes early in their course before clinical manifestation so that preemptive treatment can be undertaken; (2) refine the assessment of cardiovascular disease so as to better identify optimal medical or surgical therapies; and (3) enhance the evaluation and monitoring of the hemodynamic impact of different treatment options.

  • 282.
    Hope, Michael D.
    et al.
    University of California, San Francisco, USA.
    Wrenn, S. Jarrett
    University of California, San Francisco, USA.
    Dyverfeldt, Petter
    University of California, San Francisco, USA.
    Clinical Applications of Aortic 4D Flow Imaging2013In: Current Cardiovascular Imaging Reports, ISSN 1941-9066, Vol. 6, no 2, p. 128-139Article in journal (Refereed)
    Abstract [en]

    Quantitative aortic magnetic resonance (MR) blood flow imaging is a rapidly advancing technique that is likely to impact clinical medicine in the near future. The acquisition of comprehensive 4D velocity datasets is now possible in a clinically acceptable time frame. Unique and intuitive visualization methods are available. A number of important hemodynamic biomarkers can be derived from the data, and exploited to help understand how abnormal flow is inter-related with aortic pathology. Initial data suggest that some of the derived biomarkers can refine the clinical assessment of aortic disease and predict disease progression. We provide an overview of aortic imaging with emphasis on how flow imaging is currently used, discuss the fundamental technical aspects of multidimensional MR flow imaging, introduce key hemodynamic markers, and show how this type of imaging may soon be used for the early identification of patients at risk for the development of potentially devastating aortic complications.

  • 283. Hubbert, Laila
    et al.
    Peterzén, Bengt
    Ahn, Henrik
    Janerot-Sjoberg, Birgitta
    Second harmonic echocardiography and spontaneous contrast during implantation of a left ventricular assist device2010In: ASAIO journal (1992), ISSN 1058-2916, E-ISSN 1538-943X, Vol. 56, no 5, p. 417-21Article in journal (Refereed)
    Abstract [en]

    Implantable mechanical left ventricular assist devices (LVADs) are used as a bridge or alternative to heart transplantation. Peroperative transesophageal echocardiography is commonly applied during implantation. Significant air embolism may occur as a result of air leakage at connections and anastomoses when LV filling becomes inadequate, and this must be prevented. Early suspicion and detection of air is mandatory to avoid negative circulatory effects. We hypothesized that monitoring of heart chamber size and occurrence of single air bubbles using second harmonic imaging (SHI) echocardiography may prevent risk for significant air embolism. After implantation of the LVAD in 10 calves, invasive hemodynamic monitoring and epicardial SHI were performed while increasing pump speed. Air bubbles in the ascending aorta were monitored and the left heart visualized for off-line dimensional analysis. Detection of air bubbles in the ascending aorta preceded their appearance in the left ventricle. They occurred exclusively but not always after a decrease in left atrial (LA) size. Decrease in LA pressure did not predict bubble detection or reduction in LA size. We conclude that SHI detects spontaneous ultrasound contrast during implantation of a LVAD and that a decrease in LA size is a warning that air embolism is imminent.

  • 284.
    Häggmark, Ilian
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Romell, Jenny
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Lewin, Susanne
    Öhman, Caroline
    Hertz, Hans
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics. KTH, School of Engineering Sciences (SCI), Physics. KTH, School of Biotechnology (BIO), Centres, Albanova VinnExcellence Center for Protein Technology, ProNova.
    Cellular-Resolution Imaging of Microstructures in Rat Bone using Laboratory Propagation-Based Phase-Contrast X-ray Tomography2018In: Microscopy and Microanalysis, 2018, Vol. 24, p. 368-369Conference paper (Refereed)
  • 285.
    Häggmark, Ilian
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Vågberg, William
    Hertz, Hans
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Burvall, Anna
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Comparison of quantitative multi-material phase-retrieval algorithms in propagation-based phase-contrast X-ray tomography2017In: Optics Express, ISSN 1094-4087, E-ISSN 1094-4087, Vol. 25, no 26, p. 33543-33558Article in journal (Refereed)
    Abstract [en]

    Propagation-based phase-contrast X-ray imaging provides high-resolution, dose-efficient images of biological materials. A crucial challenge is quantitative reconstruction, referred to as phase retrieval, of multi-material samples from single-distance, and hence incomplete, data. In this work, the two most promising methods for multi-material samples, the parallel method, and the linear method, are analytically, numerically, and experimentally compared. Both methods are designed for computed tomography, as they rely on segmentation in the tomographic reconstruction. The methods are found to result in comparable image quality, but the linear method provides faster reconstruction. In addition, as already done for the parallel method, we show that the linear method provides quantitative reconstruction for monochromatic radiation.

  • 286.
    Häggmark, Ilian
    et al.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Vågberg, William
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Hertz, Hans M.
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Burvall, Anna
    KTH, School of Engineering Sciences (SCI), Applied Physics, Biomedical and X-ray Physics.
    Biomedical Applications of Multi-Material Phase Retrieval in Propagation-Based Phase-Contrast Imaging2018In: Microscopy and Microanalysis, Cambridge University Press, 2018, Vol. 24, p. 370-371Conference paper (Refereed)
  • 287.
    Häggström, Ida
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Quantitative methods for tumor imaging with dynamic PET2014Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    There is always a need and drive to improve modern cancer care. Dynamic positron emission tomography (PET) offers the advantage of in vivo functional imaging, combined with the ability to follow the physiological processes over time. In addition, by applying tracer kinetic modeling to the dynamic PET data, thus estimating pharmacokinetic parameters associated to e.g. glucose metabolism, cell proliferation etc., more information about the tissue's underlying biology and physiology can be determined. This supplementary information can potentially be a considerable aid when it comes to the segmentation, diagnosis, staging, treatment planning, early treatment response monitoring and follow-up of cancerous tumors.

    We have found it feasible to use kinetic parameters for semi-automatic tumor segmentation, and found parametric images to have higher contrast compared to static PET uptake images. There are however many possible sources of errors and uncertainties in kinetic parameters obtained through compartment modeling of dynamic PET data. The variation in the number of detected photons caused by the random nature of radioactive decay, is of course always a major source. Other sources may include: the choice of an appropriate model that is suitable for the radiotracer in question, camera detectors and electronics, image acquisition protocol, image reconstruction algorithm with corrections (attenuation, random and scattered coincidences, detector uniformity, decay) and so on. We have found the early frame sampling scheme in dynamic PET to affect the bias and uncertainty in calculated kinetic parameters, and that scatter corrections are necessary for most but not all parameter estimates. Furthermore, analytical image reconstruction algorithms seem more suited for compartment modeling applications compared to iterative algorithms.

    This thesis and included papers show potential applications and tools for quantitative pharmacokinetic parameters in oncology, and help understand errors and uncertainties associated with them. The aim is to contribute to the long-term goal of enabling the use of dynamic PET and pharmacokinetic parameters for improvements of today's cancer care.

  • 288.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    A Monte Carlo study of the dependence of early frame sampling on uncertainty and bias in pharmacokinetic parameters from dynamic PET2015In: Journal of Nuclear Medicine Technology, ISSN 0091-4916, E-ISSN 1535-5675, Vol. 43, no 1, p. 53-60Article in journal (Refereed)
    Abstract [en]

    Compartmental modeling of dynamic PET data enables quantifi- cation of tracer kinetics in vivo, through the calculated model parameters. In this study, we aimed to investigate the effect of early frame sampling and reconstruction method on pharmacokinetic parameters obtained from a 2-tissue model, in terms of bias and uncertainty (SD). Methods: The GATE Monte Carlo software was used to simulate 2 · 15 dynamic 3′-deoxy-3′-18F-fluorothymidine (18F-FLT) brain PET studies, typical in terms of noise level and kinetic parameters. The data were reconstructed by both 3- dimensional (3D) filtered backprojection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM) into 6 dynamic image sets with different early frame durations of 1, 2, 4, 6, 10, and 15 s. Bias and SD were evaluated for fitted parameter estimates, calculated from regions of interest. Results: The 2-tissue-model parameter estimates K1, k2, and fraction of arterial blood in tissue depended on early frame sampling, and a sampling of 6–15 s generally minimized bias and SD. The shortest sampling of 1 s yielded a 25% and 42% larger bias than the other schemes, for 3DRP and OSEM, respectively, and a parameter uncertainty that was 10%–70% higher. The schemes from 4 to 15 s were generally not significantly different in regards to bias and SD. Typically, the reconstruction method 3DRP yielded less framesampling dependence and less uncertain results, compared with OSEM, but was on average more biased. Conclusion: Of the 6 sampling schemes investigated in this study, an early frame duration of 6–15 s generally kept both bias and uncertainty to a minimum, for both 3DRP and OSEM reconstructions. Veryshort frames of 1 s should be avoided because they typically resulted in the largest parameter bias and uncertainty. Furthermore, 3DRP may be p

  • 289.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics. Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Beattie, Bradley J
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies2016In: Medical physics (Lancaster), ISSN 0094-2405, Vol. 43, no 6, p. 3104-3116Article in journal (Refereed)
    Abstract [en]

    Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator ofTracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment,postprocessing choices, etc., on dynamic and parametric images.

    Methods: The tool was developed in PETSTEP using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated foreach voxel of the input parametric image, whereby effects of imaging system blurring, counting noise,scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed intoimages according to the user specified method, settings, and corrections. Reconstructed images werecompared to MC data, and simple Gaussian noised time activity curves (GAUSS).

    Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root meansquare error that was within 4% on average of that of MC images, whereas the GAUSS images werewithin 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatterplot histograms, and statistically by tumor region of interest histogram comparisons that showed nosignificant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreedbetter with MC.

    Conclusions: The authors have developed a fast and easy one-stop solution for simulationsof dynamic PET and parametric images, and demonstrated that it generates both images andsubsequent parametric images with very similar noise properties to those of MC images, in afraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, andrealistic results, however since it uses simple scatter and random models it may not be suitablefor studies investigating these phenomena. dPETSTEP can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

  • 290.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Östlund, Nils
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Semi-automatic tumour segmentation by selective navigation in a three-parameter volume, obtained by voxel-wise kinetic modelling of 11C-acetate2010In: Radiation Protection Dosimetry, ISSN 0144-8420, E-ISSN 1742-3406, Vol. 139, no 1-3, p. 214-218Article in journal (Refereed)
    Abstract [en]

    Positron emission tomography (PET) is increasingly used for delineation of tumour tissue in, for example, radiotherapy treatment planning. The most common method used is to outline volumes with a certain per cent uptake over background in a static image. However, PET data can also be collected dynamically and analysed by kinetic models, which potentially represent the underlying biology better. In the present study, a three-parameter kinetic model was used for voxel-wise evaluation of (11)C-acetate data of head/neck tumours. These parameters which represent the tumour blood volume, the uptake rate and the clearance rate of the tissue were derived for each voxel using a linear regression method and used for segmentation of active tumour tissue. This feasibility study shows that it is possible to segment images based on derived model parameters. There is, however, room for improvements concerning the PET data acquisition, noise reduction and the kinetic modelling. In conclusion, this early study indicates a strong potential of the method even though no 'true' tumour volume was available for validation.

  • 291.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Axelsson, Jan
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Garpebring, Anders
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Johansson, Lennart
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C. Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Sörensen, Jens
    Medical Sciences, Nuclear Medicine, Uppsala University Hospital, Uppsala, Sweden.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    The influence of time sampling scheme on kinetic parameters obtained from compartmental modeling of a dynamic PET study: a Monte Carlo study2012In: IEEE Nuclear Science Symposium Conference Record / [ed] B. Yu, Anaheim: IEEE conference proceedings, 2012, p. 3101-3107Conference paper (Refereed)
    Abstract [en]

    Compartmental modeling of dynamic PET data enables quantification of tracer kinetics in vivo, through the obtained model parameters. The dynamic data is sorted into frames during or after the acquisition, with a sampling interval usually ranging from 10 s to 300 s. In this study we wanted to investigate the effect of the chosen sampling interval on kinetic parameters obtained from a 2-tissue model, in terms of bias and standard deviation, using a complete Monte Carlo simulated dynamic F-18-FLT PET study. The results show that the bias and standard deviation in parameter K-1 is small regardless of sampling scheme or noise in the time-activity curves (TACs), and that the bias and standard deviation in k(4) is large for all cases. The bias in V-a is clearly dependent on sampling scheme, increasing for increased sampling interval. In general, a too short sampling interval results in very noisy images and a large bias of the parameter estimate, and a too long sampling interval also increases bias. Noise in the TACs is the largest source of bias.

  • 292.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Compartment Modeling of Dynamic Brain PET: The Effect of Scatter Corrections on Parameter Errors2014Conference paper (Other academic)
    Abstract [en]

    Purpose: To investigate the effects of corrections for random and scattered coincidences on kinetic parameters in brain tumors, by using ten Monte Carlo (MC) simulated dynamic FLT-PET brain scans.

     

    Methods: The GATE MC software was used to simulate ten repetitions of a 1 hour dynamic FLT-PET scan of a voxelized head phantom. The phantom comprised six normal head tissues, plus inserted regions for blood and tumor tissue. Different time-activity-curves (TACs) for all eight tissue types were used in the simulation and were generated in Matlab using a 2-tissue model with preset parameter values (K1,k2,k3,k4,Va,Ki). The PET data was reconstructed into 28 frames by both ordered-subset expectation maximization (OSEM) and 3D filtered back-projection (3DFBP). Five image sets were reconstructed, all with normalization and different additional corrections C (A=attenuation, R=random, S=scatter): Trues (AC), trues+randoms (ARC), trues+scatters (ASC), total counts (ARSC) and total counts (AC). Corrections for randoms and scatters were based on real random and scatter sinograms that were back-projected, blurred and then forward projected and scaled to match the real counts. Weighted non-linear-least-squares fitting of TACs from the blood and tumor regions was used to obtain parameter estimates.

     

    Results: The bias was not significantly different for trues (AC), trues+randoms (ARC), trues+scatters (ASC) and total counts (ARSC) for either 3DFBP or OSEM (p<0.05). Total counts with only AC stood out however, with an up to 160% larger bias. In general, there was no difference in bias found between 3DFBP and OSEM, except in parameter Va and Ki.

     

    Conclusion: According to our results, the methodology of correcting the PET data for randoms and scatters performed well for the dynamic images where frames have much lower counts compared to static images. Generally, no bias was introduced by the corrections and their importance was emphasized since omitting them increased bias extensively.

  • 293.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York 10065.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences, Radiation Physics.
    Compartment modeling of dynamic brain PET: the impact of scatter corrections on parameter errors2014In: Medical physics, ISSN 0094-2405, Vol. 41, no 11, p. 111907-Article in journal (Refereed)
    Abstract [en]

    Purpose: The aim of this study was to investigate the effect of scatter and its correction on kinetic parameters in dynamic brain positron emission tomography (PET) tumor imaging. The 2-tissue compartment model was used, and two different reconstruction methods and two scatter correction (SC) schemes were investigated.

    Methods: The gate Monte Carlo (MC) softwarewas used to perform 2×15 full PET scan simulations of a voxelized head phantom with inserted tumor regions. The two sets of kinetic parameters of all tissues were chosen to represent the 2-tissue compartment model for the tracer 3′-deoxy- 3′-(18F)fluorothymidine (FLT), and were denoted FLT1 and FLT2. PET data were reconstructed with both 3D filtered back-projection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM). Images including true coincidences with attenuation correction (AC) and true+scattered coincidences with AC and with and without one of two applied SC schemes were reconstructed. Kinetic parameters were estimated by weighted nonlinear least squares fitting of image derived time–activity curves. Calculated parameters were compared to the true input to the MC simulations.

    Results: The relative parameter biases for scatter-eliminated data were 15%, 16%, 4%, 30%, 9%, and 7% (FLT1) and 13%, 6%, 1%, 46%, 12%, and 8% (FLT2) for K1, k2, k3, k4,Va, and Ki, respectively. As expected, SC was essential for most parameters since omitting it increased biases by 10 percentage points on average. SC was not found necessary for the estimation of Ki and k3, however. There was no significant difference in parameter biases between the two investigated SC schemes or from parameter biases from scatter-eliminated PET data. Furthermore, neither 3DRP nor OSEM yielded the smallest parameter biases consistently although therewas a slight favor for 3DRP which produced less biased k3 and Ki estimates while OSEM resulted in a less biased Va. The uncertainty in OSEM parameterswas about 26% (FLT1) and 12% (FLT2) larger than for 3DRP although identical postfilters were applied.

    Conclusions: SC was important for good parameter estimations. Both investigated SC schemes performed equally well on average and properly corrected for the scattered radiation, without introducing further bias. Furthermore, 3DRP was slightly favorable over OSEM in terms of kinetic parameter biases and SDs.

  • 294.
    Häggström, Ida
    et al.
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Schmidtlein, C Ross
    Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, USA.
    Karlsson, Mikael
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Larsson, Anne
    Umeå University, Faculty of Medicine, Department of Radiation Sciences.
    Do scatter and random corrections affect the errors in kinetic parameters in dynamic PET?: a Monte Carlo study2013In: 2013 IEEE Nuclear Science Symposium and Medical Imaging Conference (2013 NSS/MIC), IEEE conference proceedings, 2013, , p. 4Conference paper (Refereed)
    Abstract [en]

    Dynamic positron emission tomography (PET) data can be evaluated by compartmental models, yielding model specific kinetic parameters. For the parameters to be of quantitative use however, understanding and estimation of errors and uncertainties associated with them are crucial.

    The aim in this study was to investigate the effects of the inclusion of scattered and random counts and their respective corrections on kinetic parameter errors.

    The MC software GATE was used to simulate two dynamic PET scans of a phantom containing three regions; blood, tissue and a static background. The two sets of time-activity-curves (TACs) used were generated for a 2-tissue compartment model with preset parameter values (K1, k2, k3, k4 and Va). The PET data was reconstructed into 19 frames by both ordered-subset expectation maximization (OSEM) and 3D filtered back-projection with reprojection (3DFBPRP) with normalization and additional corrections (A=attenuation, R=random, S=scatter, C=correction): True counts (AC), true+random counts (ARC), true+scattered counts (ASC) and total counts (ARSC).

    The results show that parameter estimates from true counts (AC), true+random counts (ARC), true+scattered counts (ASC) and total counts (ARSC) were not significantly different, with the exception of Va where the bias increased with added corrections. Thus, the inclusion of and correction for scattered and random counts did not affect the bias in parameter estimates K1, k2, k3, k4 and Ki. Uncorrected total counts (only AC) resulted in biases of hundreds or even thousands of percent, emphasizing the need for proper corrections. Reconstructions with 3DFBPRP resulted in overall 20-40% less biased estimates compared to OSEM.

  • 295.
    Härd, Victoria
    Linköping University, Department of Electrical Engineering, Computer Vision.
    Automatic Alignment of 2D Cine Morphological Images Using 4D Flow MRI Data2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    Cardiovascular diseases are among the most common causes of death worldwide. One of the recently developed flow analysis technique called 4D flow magnetic resonance imaging (MRI) allows an early detection of such diseases. Due to the limited resolution and contrast between blood pool and myocardium of 4D flow images, cine MR images are often used for cardiac segmentation. The delineated structures are then transferred to the 4D Flow images for cardiovascular flow analysis. Cine MR images are however acquired with multiple breath-holds, which can be challenging for some people, especially, when a cardiovascular disease is present. Consequently, unexpected breathing motion by a patient may lead to misalignments between the acquired cine MR images.

    The goal of the thesis is to test the feasibility of an automatic image registration method to correct the misalignment caused by respiratory motion in morphological 2D cine MR images by using the 4D Flow MR as the reference image. As a registration method relies on a set of optimal parameters to provide desired results, a comprehensive investigation was performed to find such parameters. Different combinations of registration parameters settings were applied on 20 datasets from both healthy volunteers and patients. The best combinations, selected on the basis of normalized cross-correlation, were evaluated using the clinical gold-standard by employing widely used geometric measures of spatial correspondence. The accuracy of the best parameters from geometric evaluation was finally validated by using simulated misalignments.

    Using a registration method consisting of only translation improved the results for both datasets from healthy volunteers and patients and the simulated misalignment data. For the datasets from healthy volunteers and patients, the registration improved the results from 0.7074 ± 0.1644 to 0.7551 ± 0.0737 in Dice index and from 1.8818 ± 0.9269 to 1.5953 ± 0.5192 for point-to-curve error. These values are a mean value for all the 20 datasets.

    The results from geometric evaluation on the data from both healthy volunteers and patients show that the developed correction method is able to improve the alignment of the cine MR images. This allows a reliable segmentation of 4D flow MR images for cardiac flow assessment.

  • 296. Imura, Masataka
    et al.
    Kuroda, Tomohiro
    Oshiro, O
    Chihara, Kunihiro
    Brandberg, John
    Ask, Per
    Linköping University, Department of Biomedical Engineering, Physiological Measurements. Linköping University, The Institute of Technology.
    Blood flow visualization in immersive environment based on color Doppler images2001In: PROCEEDINGS OF THE 23RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY, VOLS 1-4: BUILDING NEW BRIDGES AT THE FRONTIERS OF ENGINEERING AND MEDICINE, 2001, Vol. 23, p. 3167-3170Conference paper (Refereed)
    Abstract [en]

    An accurate grasp of blood flow patterns in a human heart is important to evaluate cardiac diseases of patients. Doppler ultrasound method is widely used to visualize blood flow patterns and has obtained excellent results in diagnosis. However, the output from Doppler ultrasound method is usually represented as a two-dimensional image, though blood flow patterns have three-dimensional complex structure and change dynamically. Therefore, improvement of both data acquisition and data visualization techniques is indispensable to diagnosis of cardiac faculty. It is worth mentioning that visualization also dominates the level of understanding as data acquisition, because poor visualization ruins the value of the most accurate result of measurement as if it were nothing. The authors construct an interactive visualization system suitable for three-dimensional blood flow, utilizing the immersive projection display. With the developed visualization system, which possesses interactivity and a wide field of view, users can easily understand the state of entire flow, such as the occurrence of turbulence, and the patterns of blood flow.

  • 297.
    Ishaq, Omer
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Elf, Johan
    Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational and Systems Biology.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    An Evaluation of the Faster STORM Method for Super-resolution Microscopy2014In: Proceedings of the 22nd International Conference on Pattern Recognition, 2014, p. 4435-4440Conference paper (Refereed)
    Abstract [en]

    Development of new stochastic super-resolution methods together with fluorescence microscopy imaging enables visualization of biological processes at increasing spatial and temporal resolution. Quantitative evaluation of such imaging experiments call for computational analysis methods that localize the signals with high precision and recall. Furthermore, it is desirable that the methods are fast and possible to parallelize so that the ever increasing amounts of collected data can be handled in an efficient way. We here in address signal detection in super-resolution microscopy by approaches based on compressed sensing. We describe how a previously published approach can be parallelized, reducing processing time at least four times. We also evaluate the effect of a greedy optimization approach on signal recovery at high noise and molecule density. Furthermore, our evaluation reveals how previously published compressed sensing algorithms have a performance that degrades to that of a random signal detector at high molecule density. Finally, we show the approximation of the imaging system's point spread function affects recall and precision of signal detection, illustrating the importance of parameter optimization. We evaluate the methods on synthetic data with varying signal to noise ratio and increasing molecular density, and visualize performance on realsuper-resolution microscopy data from a time-lapse sequence of livingcells.

  • 298.
    Ishaq, Omer
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Negri, Joseph
    Bray, Mark-Anthony
    Pacureanu, Alexandra
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Peterson, Randall T.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Automated quantification of Zebrafish tail deformation for high-throughput drug screening2013In: Proc. 10th International Symposium on Biomedical Imaging: From Nano to Macro, Piscataway, NJ: IEEE , 2013, p. 902-905Conference paper (Refereed)
  • 299.
    Issac Niwas, Swamidoss
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kårsnäs, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Uhlmann, Virginie
    Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA, USA and Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
    Palanisamy, P.
    Dept. of Electronics and Communication Engineering (ECE), National Institute of Technology (NIT), Tiruchirappalli, India.
    Kampf, Caroline
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Molecular and Morphological Pathology.
    Simonsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab.
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas2012In: Histopathology Image Analysis (HIMA): a MICCAI 2012 workshop, 2012Conference paper (Refereed)
    Abstract [en]

    Background:

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/ ). It contains a large number of histological images of sections from human tissue. Tissue micro arrays are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples.

    Methods and Material:

    The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features and WND-CHARM-inspired features. The extracted features are used into two different multivariate classifiers (SVM and LDA classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue.

    Results:

    Good results have been obtained by using the combinations of GLCM and wavelets and texture features, edge features, histograms, transforms, etc. (WND-CHARM). The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert.

    Conclusions:

    Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumour grading.

  • 300.
    Issac Niwas, Swamidoss
    et al.
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Kårsnäs, Andreas
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Uhlmann, Virginie
    Imaging Platform, Broad Institute of Harvard and MIT, Cambridge, Massachusetts MA, USA and Biomedical Imaging Group, École Polytechnique Fédérale de Lausanne (EPFL), Switzerland.
    Ponnusamy, Palanisamy
    Dept. of Electronics and Communication Engineering (ECE), National Institute of Technology (NIT), Tiruchirappalli, India.
    Kampf, Caroline
    Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Genetics and Pathology, Molecular and Morphological Pathology.
    Simonsson, Martin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Wählby, Carolina
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Institute of Harvard and Massachusetts Institute Technology (MIT), Cambridge, Massachusetts, MA, USA, .
    Strand, Robin
    Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Visual Information and Interaction. Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Computerized Image Analysis and Human-Computer Interaction.
    Automated classification of immunostaining patterns in breast tissue from the Human Protein Atlas2013In: Journal of Pathology Informatics, ISSN 2229-5089, E-ISSN 2153-3539, Vol. 4, no 14Article in journal (Refereed)
    Abstract [en]

    Background:

    The Human Protein Atlas (HPA) is an effort to map the location of all human proteins (http://www.proteinatlas.org/). It contains a large number of histological images of sections from human tissue. Tissue micro arrays (TMA) are imaged by a slide scanning microscope, and each image represents a thin slice of a tissue core with a dark brown antibody specific stain and a blue counter stain. When generating antibodies for protein profiling of the human proteome, an important step in the quality control is to compare staining patterns of different antibodies directed towards the same protein. This comparison is an ultimate control that the antibody recognizes the right protein. In this paper, we propose and evaluate different approaches for classifying sub-cellular antibody staining patterns in breast tissue samples.

    Materials and Methods:

    The proposed methods include the computation of various features including gray level co-occurrence matrix (GLCM) features, complex wavelet co-occurrence matrix (CWCM) features, and weighted neighbor distance using compound hierarchy of algorithms representing morphology (WND-CHARM)-inspired features. The extracted features are used into two different multivariate classifiers (support vector machine (SVM) and linear discriminant analysis (LDA) classifier). Before extracting features, we use color deconvolution to separate different tissue components, such as the brownly stained positive regions and the blue cellular regions, in the immuno-stained TMA images of breast tissue.

    Results:

    We present classification results based on combinations of feature measurements. The proposed complex wavelet features and the WND-CHARM features have accuracy similar to that of a human expert.

    Conclusions:

    Both human experts and the proposed automated methods have difficulties discriminating between nuclear and cytoplasmic staining patterns. This is to a large extent due to mixed staining of nucleus and cytoplasm. Methods for quantification of staining patterns in histopathology have many applications, ranging from antibody quality control to tumor grading.

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