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DIRA-3D-a model-based iterative algorithm for accurate dual-energy dual-source 3D helical CT
Linköping University, Department of Electrical Engineering, Computer Vision. Linköping University, Faculty of Science & Engineering. Linköping University, Center for Medical Image Science and Visualization (CMIV). Region Östergötland, Center for Diagnostics, Medical radiation physics.ORCID iD: 0000-0002-9072-2204
Linköping University, Department of Medical and Health Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Diagnostics, Medical radiation physics.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Karolinska Univ, Sweden.
Linköping University, Department of Medical and Health Sciences, Division of Radiological Sciences. Linköping University, Faculty of Medicine and Health Sciences. Region Östergötland, Center for Surgery, Orthopaedics and Cancer Treatment, Department of Radiation Physics. Linköping University, Center for Medical Image Science and Visualization (CMIV).ORCID iD: 0000-0003-0209-498X
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2019 (English)In: BIOMEDICAL PHYSICS and ENGINEERING EXPRESS, ISSN 2057-1976, Vol. 5, no 6, article id UNSP 065005Article in journal (Refereed) Published
Abstract [en]

Quantitative dual-energy computed tomography may improve the accuracy of treatment planning in radiation therapy. Of special interest are algorithms that can estimate material composition of the imaged object. One example of such an algorithm is the 2D model-based iterative reconstruction algorithm DIRA. The aim of this work is to extend this algorithm to 3D so that it can be used with cone-beams and helical scanning. In the new algorithm, the parallel FBP method was replaced with the approximate 3D FBP-based PI-method. Its performance was tested using a mathematical phantom consisting of six ellipsoids. The algorithm substantially reduced the beam-hardening artefact and the artefacts caused by approximate reconstruction after six iterations. Compared to Alvarez-Macovskis base material decomposition, DIRA-3D does not require geometrically consistent projections and hence can be used in dual-source CT scanners. Also, it can use several tissue-specific material bases at the same time to represent the imaged object.

Place, publisher, year, edition, pages
IOP PUBLISHING LTD , 2019. Vol. 5, no 6, article id UNSP 065005
Keywords [en]
energy computed tomography; model-based iterative reconstruction; material composition
National Category
Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-161626DOI: 10.1088/2057-1976/ab42eeISI: 000487561400005OAI: oai:DiVA.org:liu-161626DiVA, id: diva2:1367890
Note

Funding Agencies|Swedish Cancer Foundation [CAN 2015/618, CAN 2017/1029, CAN 2018/622]; ALF Grants Region Ostergotland [LiO-724181, LiO-697941, LiO-602731, LiO-438731]; Swedish Research CouncilSwedish Research Council [VR-NT 2016-05033]; Medical Faculty at Linkoping University; Patientsakerhetsforskning [LiO-724181]

Available from: 2019-11-05 Created: 2019-11-05 Last updated: 2019-12-13

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Magnusson, MariaBjörnfot, MagnusCarlsson Tedgren, ÅsaAlm Carlsson, GudrunSandborg, MichaelMalusek, Alexandr
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Computer VisionFaculty of Science & EngineeringCenter for Medical Image Science and Visualization (CMIV)Medical radiation physicsDepartment of Medical and Health SciencesFaculty of Medicine and Health SciencesDivision of Radiological SciencesDepartment of Radiation Physics
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