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New vessel analysis tool for morphometric quantification and visualization of vessels in CT and MR imaging data sets.
Boskamp T, Rinck D, Link F, Kümmerlen B, Stamm G, Mildenberger P.
MeVis Center for Medical Diagnostic Systems and Visualization, Universitätsallee 29, 28359 Bremen, Germany. tboskamp@mevis.de
Radiographics. 2004 Jan-Feb;24(1):287-97.
Image processing algorithms and a prototypical research software tool have been developed for visualization and quantitative analysis of vessels in data sets from computed tomography and magnetic resonance imaging. The software is based on a sequence of processing steps, which are as follows: (a) vessel segmentation based on a region growing algorithm, (b) interactive "premasking" to optionally exclude interfering structures close to the vessels of interest, (c) distance transform-based skeletonization, (d) multiplanar reformation orthogonal to the vessel path, (e) identification of the lumen boundary on the orthogonal cross-section images, and (f) morphometric measurements. The development of the algorithmic components and the application user interface has been carried out in close cooperation with clinical users to achieve a high degree of usability and flexible support of work flow. The software has been successfully applied to the intracranial arteries, carotid arteries, and abdominal and thoracic aorta, as well as the renal, coronary, and peripheral arteries. Copyright RSNA, 2004
Posted via PubMed for educational and discussion purposes only.
Link to PubMed Reference
MeVis Center for Medical Diagnostic Systems and Visualization, Universitätsallee 29, 28359 Bremen, Germany. tboskamp@mevis.de
Radiographics. 2004 Jan-Feb;24(1):287-97.
Image processing algorithms and a prototypical research software tool have been developed for visualization and quantitative analysis of vessels in data sets from computed tomography and magnetic resonance imaging. The software is based on a sequence of processing steps, which are as follows: (a) vessel segmentation based on a region growing algorithm, (b) interactive "premasking" to optionally exclude interfering structures close to the vessels of interest, (c) distance transform-based skeletonization, (d) multiplanar reformation orthogonal to the vessel path, (e) identification of the lumen boundary on the orthogonal cross-section images, and (f) morphometric measurements. The development of the algorithmic components and the application user interface has been carried out in close cooperation with clinical users to achieve a high degree of usability and flexible support of work flow. The software has been successfully applied to the intracranial arteries, carotid arteries, and abdominal and thoracic aorta, as well as the renal, coronary, and peripheral arteries. Copyright RSNA, 2004
Posted via PubMed for educational and discussion purposes only.
Link to PubMed Reference
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