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Segmentation with gray-scale connectedness can separate arteries and veins in MRA
Linköping University, Faculty of Health Sciences. Linköping University, Department of Medicine and Care, Radiology. Östergötlands Läns Landsting, Centre for Medical Imaging, Department of Radiology UHL. Linköping University, Center for Medical Image Science and Visualization, CMIV.ORCID iD: 0000-0002-7750-1917
2002 (English)In: Journal of Magnetic Resonance Imaging, ISSN 1053-1807, E-ISSN 1522-2586, Vol. 15, no 4, 438-445 p.Article in journal (Refereed) Published
Abstract [en]

Purpose: To describe and present some preliminary results for a novel algorithm for segmentation with gray-scale connectedness as a means to separate arteries and veins in magnetic resonance angiography (MRA). Materials and Methods: The proposed algorithm, SeparaSeed, uses the gray-scale degree of connectedness as a tool to find the zone surrounding each vessel, in order to split the original volume into its different vessel components. In contrast to traditional segmentation methods, no gray-scale information is lost in the process. The segmentation is performed in one step, resulting in a partition of the initial volume into a chosen number of regions of interest (ROIs). Finally. visualization is achieved by projecting the 3D vessel trees to 2D using the common maximum intensity projection (MIP). The algorithm was tested in two MRA data sets of the vessels of the pelvis acquired after injection of an intravascular contrast agent and in one data set of the vessels of the neck with gadolinium. Results: In all data sets, a large proportion of the venous signal was removed while preserving that of the arteries, thus improving visualization of the relevant vessels. Conclusion: Separation of arteries and veins is feasible with the proposed algorithm with a moderate amount of interaction. ⌐ 2002 Wiley-Liss, Inc.

Place, publisher, year, edition, pages
2002. Vol. 15, no 4, 438-445 p.
National Category
Medical and Health Sciences
URN: urn:nbn:se:liu:diva-27134DOI: 10.1002/jmri.10047Local ID: 11782OAI: diva2:247685
Available from: 2009-10-08 Created: 2009-10-08 Last updated: 2013-09-05

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Smedby, Örjan
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Faculty of Health SciencesRadiologyDepartment of Radiology UHLCenter for Medical Image Science and Visualization, CMIV
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Journal of Magnetic Resonance Imaging
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