Tracking-based Segmentation and Volume Rendering for Assessing Stenosis of Coronary Arteries in MS-CTA Images
Mueller, Daniel, Maeder, Anthony J., & O'Shea, Peter J. (2007) Tracking-based Segmentation and Volume Rendering for Assessing Stenosis of Coronary Arteries in MS-CTA Images. In Gobbetti, E. (Ed.) Computer Graphics and Imaging (CGIM), February 13 – 15, Innsbruck, Austria.
Multi-slice spiral computed tomography angiography (MS-CTA) is emerging as a clinically robust modality for diagnosis and surgical planning for coronary heart disease. To enable these tasks the coronary arteries must be segmented and visualised. This paper proposes the use of an improved tracking-based algorithm for segmenting the coronary artery network. The segmentation results are coupled with direct volume rendering allowing for the 3-D visualisation of the degree of stenosis. We represent vessels using a generalised-cylinder model, which facilitates fast segmentation and the visualisation of vessel cross-sectional area. A number of synthetic and in vivo datasets are used to validate and demonstrate the approach.
Impact and interest:
Citation countsare sourced monthly fromand citation databases.
These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.
Citations counts from theindexing service can be viewed at the linked Google Scholar™ search.
Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.
|Item Type:||Conference Paper|
|Keywords:||Imaging and Image Processing, Vessel Segmentation, Volume Rendering, Medical Imaging|
|Subjects:||Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)|
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > BIOMEDICAL ENGINEERING (090300) > Biomedical Instrumentation (090303)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Graphics (080103)
|Divisions:||Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering|
|Copyright Owner:||Copyright 2007 ACTA Press|
|Copyright Statement:||Reproduced in accordance with the copyright policy of the publisher.|
|Deposited On:||12 Mar 2007|
|Last Modified:||01 Sep 2014 10:04|
Repository Staff Only: item control page