Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Level Set Segmentation and Volume Visualization of Vascular Trees
Linköping University, Department of Science and Technology, Media and Information Technology. Linköping University, Center for Medical Image Science and Visualization (CMIV). Linköping University, The Institute of Technology.ORCID iD: 0000-0002-6457-4914
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Medical imaging is an important part of the clinical workflow. With the increasing amount and complexity of image data comes the need for automatic (or semi-automatic) analysis methods which aid the physician in the exploration of the data. One specific imaging technique is angiography, in which the blood vessels are imaged using an injected contrast agent which increases the contrast between blood and surrounding tissue. In these images, the blood vessels can be viewed as tubular structures with varying diameters. Deviations from this structure are signs of disease, such as stenoses introducing reduced blood flow, or aneurysms with a risk of rupture. This thesis focuses on segmentation and visualization of blood vessels, consituting the vascular tree, in angiography images.

Segmentation is the problem of partitioning an image into separate regions. There is no general segmentation method which achieves good results for all possible applications. Instead, algorithms use prior knowledge and data models adapted to the problem at hand for good performance. We study blood vessel segmentation based on a two-step approach. First, we model the vessels as a collection of linear structures which are detected using multi-scale filtering techniques. Second, we develop machine-learning based level set segmentation methods to separate the vessels from the background, based on the output of the filtering.

In many applications the three-dimensional structure of the vascular tree has to be presented to a radiologist or a member of the medical staff. For this, a visualization technique such as direct volume rendering is often used. In the case of computed tomography angiography one has to take into account that the image depends on both the geometrical structure of the vascular tree and the varying concentration of the injected contrast agent. The visualization should have an easy to understand interpretation for the user, to make diagnostical interpretations reliable. The mapping from the image data to the visualization should therefore closely follow routines that are commonly used by the radiologist. We developed an automatic method which adapts the visualization locally to the contrast agent, revealing a larger portion of the vascular tree while minimizing the manual intervention required from the radiologist. The effectiveness of this method is evaluated in a user study involving radiologists as domain experts.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013. , 86 p.
Series
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1543
Keyword [en]
level set methods, image segmentation, edge detection, visualization, volume rendering, blood vessels, angiography, vascular trees
National Category
Media and Communication Technology Medical Image Processing
Identifiers
URN: urn:nbn:se:liu:diva-97371ISBN: 978-91-7519-514-8 (print)OAI: oai:DiVA.org:liu-97371DiVA: diva2:647248
Public defence
2013-10-21, Domteatern, Visualiseringscenter C, Kungsgatan 54, Norrköping, 14:00 (English)
Opponent
Supervisors
Available from: 2013-09-11 Created: 2013-09-10 Last updated: 2016-08-31Bibliographically approved
List of papers
1. Flexible and Topologically Localized Segmentation
Open this publication in new window or tab >>Flexible and Topologically Localized Segmentation
2007 (English)In: EuroVis07 Joint Eurographics: IEEE VGTC Symposium on Visualization / [ed] Ken Museth, Torsten Möller, and Anders Ynnerman, Aire-la-Ville, Switzerland: Eurographics Association , 2007, , 179-186 p.179-186 p.Conference paper, Published paper (Refereed)
Abstract [en]

One of the most common visualization tasks is the extraction of significant boundaries, often performed with iso- surfaces or level set segmentation. Isosurface extraction is simple and can be guided by geometric and topological analysis, yet frequently does not extract the desired boundary. Level set segmentation is better at boundary extrac- tion, but either leads to global segmentation without edges, [CV01], that scales unfavorably in 3D or requires an initial estimate of the boundary from which to locally solve segmentation with edges. We propose a hybrid system in which topological analysis is used for semi-automatic initialization of a level set segmentation, and geometric information bounded topologically is used to guide and accelerate an iterative segmentation algorithm that com- bines several state-of-the-art level set terms. We thus combine and improve both the flexible isosurface interface and level set segmentation without edges.

Place, publisher, year, edition, pages
Aire-la-Ville, Switzerland: Eurographics Association, 2007. 179-186 p.
National Category
Engineering and Technology
Identifiers
urn:nbn:se:liu:diva-40841 (URN)54293 (Local ID)978-3-905673-45-6 (ISBN)54293 (Archive number)54293 (OAI)
Conference
Eurographics/ IEEE-VGTC Symposium on Visualization, 23-25 May, Norrköping, Sweden
Available from: 2009-10-10 Created: 2009-10-10 Last updated: 2013-09-19
2. Blood vessel segmentation using multi-scale quadrature filtering
Open this publication in new window or tab >>Blood vessel segmentation using multi-scale quadrature filtering
2010 (English)In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 31, no 8, 762-767 p.Article in journal (Refereed) Published
Abstract [en]

The segmentation of blood vessels is a common problem in medical imagingand various applications are found in diagnostics, surgical planning, trainingand more. Among many dierent techniques, the use of multiple scales andline detectors is a popular approach. However, the typical line lters usedare sensitive to intensity variations and do not target the detection of vesselwalls explicitly. In this article, we combine both line and edge detection usingquadrature lters across multiple scales. The lter result gives well denedvessels as linear structures, while distinct edges facilitate a robust segmentation.We apply the lter output to energy optimization techniques for segmentationand show promising results in 2D and 3D to illustrate the behavior of ourmethod. The conference version of this article received the best paper award inthe bioinformatics and biomedical applications track at ICPR 2008.

Place, publisher, year, edition, pages
Elsevier, 2010
Keyword
Image segmentation, Blood vessels, Medical imaging, Multi-scale, Quadrature filter, Level set method
National Category
Medical Laboratory and Measurements Technologies
Identifiers
urn:nbn:se:liu:diva-21046 (URN)10.1016/j.patrec.2009.09.020 (DOI)000277552600014 ()
Note
Original Publication: Gunnar Läthén, Jimmy Jonasson and Magnus Borga, Blood vessel segmentation using multi-scale quadrature filtering, 2010, Pattern Recognition Letters, (31), 8, 762-767. http://dx.doi.org/10.1016/j.patrec.2009.09.020 Copyright: Elsevier Science B.V., Amsterdam. http://www.elsevier.com/ Available from: 2009-09-28 Created: 2009-09-28 Last updated: 2017-12-13
3. Non-ring Filters for Robust Detection of Linear Structures
Open this publication in new window or tab >>Non-ring Filters for Robust Detection of Linear Structures
2010 (English)In: Proceedings of the 20th International Conference on Pattern Recognition, Los Alamitos, CA, USA: IEEE Computer Society, 2010, 233-236 p.Conference paper, Published paper (Refereed)
Abstract [en]

Many applications in image analysis include the problem of linear structure detection, e.g. segmentation of blood vessels in medical images, roads in satellite images, etc. A simple and efficient solution is to apply linear filters tuned to the structures of interest and extract line and edge positions from the filter output. However, if the filter is not carefully designed, artifacts such as ringing can distort the results and hinder a robust detection. In this paper, we study the ringing effects using a common Gabor filter for linear structure detection, and suggest a method for generating non-ring filters in 2D and 3D. The benefits of the non-ring design are motivated by results on both synthetic and natural images.

Place, publisher, year, edition, pages
Los Alamitos, CA, USA: IEEE Computer Society, 2010
Series
International Conference on Pattern Recognition, ISSN 1051-4651
Keyword
ringing filters, Gabor, non-ring filters, edge detection, filter design
National Category
Engineering and Technology Computer and Information Science Computer Vision and Robotics (Autonomous Systems) Signal Processing
Identifiers
urn:nbn:se:liu:diva-58850 (URN)10.1109/ICPR.2010.66 (DOI)978-1-4244-7542-1 (ISBN)
Conference
20th International Conference on Pattern Recognition, Istanbul, Turkey, 23-26 August 2010
Note

©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Gunnar Läthén, Olivier Cros, Hans Knutsson and Magnus Borga, Non-ring Filters for Robust Detection of Linear Structures, 2010, Proceedings of the 20th International Conference on Pattern Recognition, 233-236. http://dx.doi.org/10.1109/ICPR.2010.66

Available from: 2010-08-30 Created: 2010-08-30 Last updated: 2014-10-08Bibliographically approved
4. Modified Gradient Search for Level Set Based Image Segmentation
Open this publication in new window or tab >>Modified Gradient Search for Level Set Based Image Segmentation
2013 (English)In: IEEE Transactions on Image Processing, ISSN 1057-7149, E-ISSN 1941-0042, Vol. 22, no 2, 621-630 p.Article in journal (Refereed) Published
Abstract [en]

Level set methods are a popular way to solve the image segmentation problem. The solution contour is found by solving an optimization problem where a cost functional is minimized. Gradient descent methods are often used to solve this optimization problem since they are very easy to implement and applicable to general nonconvex functionals. They are, however, sensitive to local minima and often display slow convergence. Traditionally, cost functionals have been modified to avoid these problems. In this paper, we instead propose using two modified gradient descent methods, one using a momentum term and one based on resilient propagation. These methods are commonly used in the machine learning community. In a series of 2-D/3-D-experiments using real and synthetic data with ground truth, the modifications are shown to reduce the sensitivity for local optima and to increase the convergence rate. The parameter sensitivity is also investigated. The proposed methods are very simple modifications of the basic method, and are directly compatible with any type of level set implementation. Downloadable reference code with examples is available online.

Place, publisher, year, edition, pages
IEEE Signal Processing Society, 2013
Keyword
Active contours, gradient methods, image segmentation, level set method, machine learning, optimization, variational problems
National Category
Signal Processing Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-87658 (URN)10.1109/TIP.2012.2220148 (DOI)000314717800017 ()23014748 (PubMedID)
Available from: 2013-01-21 Created: 2013-01-21 Last updated: 2017-12-06
5. Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel Visualization
Open this publication in new window or tab >>Automatic Tuning of Spatially Varying Transfer Functions for Blood Vessel Visualization
Show others...
2012 (English)In: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 18, no 12, 2345-2354 p.Article in journal (Refereed) Published
Abstract [en]

Computed Tomography Angiography (CTA) is commonly used in clinical routine for diagnosing vascular diseases. The procedure involves the injection of a contrast agent into the blood stream to increase the contrast between the blood vessels and the surrounding tissue in the image data. CTA is often visualized with Direct Volume Rendering (DVR) where the enhanced image contrast is important for the construction of Transfer Functions (TFs). For increased efficiency, clinical routine heavily relies on preset TFs to simplify the creation of such visualizations for a physician. In practice, however, TF presets often do not yield optimal images due to variations in mixture concentration of contrast agent in the blood stream. In this paper we propose an automatic, optimization- based method that shifts TF presets to account for general deviations and local variations of the intensity of contrast enhanced blood vessels. Some of the advantages of this method are the following. It computationally automates large parts of a process that is currently performed manually. It performs the TF shift locally and can thus optimize larger portions of the image than is possible with manual interaction. The method is based on a well known vesselness descriptor in the definition of the optimization criterion. The performance of the method is illustrated by clinically relevant CT angiography datasets displaying both improved structural overviews of vessel trees and improved adaption to local variations of contrast concentration. 

Place, publisher, year, edition, pages
IEEE, 2012
National Category
Radiology, Nuclear Medicine and Medical Imaging Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-79365 (URN)10.1109/TVCG.2012.203 (DOI)000310143100038 ()
Conference
SciVis
Available from: 2012-07-15 Created: 2012-07-15 Last updated: 2017-12-07Bibliographically approved
6. Evaluation of transfer function methods in direct volume rendering of the blood vessel lumen
Open this publication in new window or tab >>Evaluation of transfer function methods in direct volume rendering of the blood vessel lumen
2014 (English)In: Proceedings from the EG VCBM 2014. Eurographics Workshop on Visual Computing for Biology and Medicine, Vienna, Austria, September 4–5, 2014 / [ed] Ivan Viola and Katja Buehler and Timo Ropinski, Eurographics - European Association for Computer Graphics, 2014, 117-126 p.Conference paper, Published paper (Refereed)
Abstract [en]

Visualization of contrast enhanced blood vessels in CT angiography data presents a challenge due to varying concentration of the contrast agent. The purpose of this work is to evaluate the correctness (effectiveness) in visualizing the vessel lumen using two different 3D visualization strategies, thereby assessing the feasibility of using such visualizations for diagnostic decisions. We compare a standard visualization approach with a recent method which locally adapts to the contrast agent concentration. Both methods are evaluated in a parallel setting where the participant is instructed to produce a complete visualization of the vessel lumen, including both large and small vessels, in cases of calcified vessels in the legs. The resulting visualizations are thereafter compared in a slice viewer to assess the correctness of the visualized lumen. The results indicate that the participants generally overestimated the size of the vessel lumen using the standard visualization, whereas the locally adaptive method better conveyed the true anatomy. The participants did find the interpretation of the locally adaptive method to be less intuitive, but also noted that this did not introduce any prohibitive complexity in the work flow. The observed trends indicate that the visualized lumen strongly depends on the width and placement of the applied transfer function and that this dependency is inherently local rather than global. We conclude that methods that permit local adjustments, such as the method investigated in this study, can be beneficial to certain types of visualizations of large vascular trees

Place, publisher, year, edition, pages
Eurographics - European Association for Computer Graphics, 2014
Series
Eurographics Workshop on Visual Computing for Biology and Medicine, ISSN 2070-5778
National Category
Medical Image Processing
Identifiers
urn:nbn:se:liu:diva-97370 (URN)10.2312/vcbm.20141197 (DOI)978-3-905674-62-0 (ISBN)
Conference
EG VCBM 2014. Eurographics Workshop on Visual Computing for Biology and Medicine, Vienna, Austria, September 4–5, 2014
Available from: 2013-09-10 Created: 2013-09-10 Last updated: 2016-08-31Bibliographically approved

Open Access in DiVA

Level Set Segmentation and Volume Visualization of Vascular Trees(4825 kB)1876 downloads
File information
File name FULLTEXT02.pdfFile size 4825 kBChecksum SHA-512
42a58de34679780869121d14a89f1d790c52df6f1b2468e9558f80b1efdfc9260c0913e0e0a2b6565aa2b27107a42ed2bac45efffb219df5f9138339535ec18e
Type fulltextMimetype application/pdf
omslag(2809 kB)38 downloads
File information
File name COVER01.pdfFile size 2809 kBChecksum SHA-512
ea9bf33f159b553a408f78db7bac63711a58c9bbe4c8428d8831a7bedc5a32284f81122081fc22451739f925c864ead28e7bd3ecb6d0bd8e1a8b95f3530524fa
Type coverMimetype application/pdf

Search in DiVA

By author/editor
Läthén, Gunnar
By organisation
Media and Information TechnologyCenter for Medical Image Science and Visualization (CMIV)The Institute of Technology
Media and Communication TechnologyMedical Image Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 1901 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 1650 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf