Automated segmentation of the left ventricle in cardiac MRI. Export

@article{citeulike:2494933, abstract = {We present a fully automated deformable model technique for myocardium segmentation in 3D MRI. Loss of signal due to blood flow, partial volume effects and significant variation of surface grey value appearance make this a difficult problem. We integrate various sources of prior knowledge learned from annotated image data into a deformable model. Inter-individual shape variation is represented by a statistical point distribution model, and the spatial relationship of the epi- and endocardium is modeled by adapting two coupled triangular surface meshes. To robustly accommodate variation of grey value appearance around the myocardiac surface, a prior parametric spatially varying feature model is established by classification of grey value surface profiles. Quantitative validation of 121 3D MRI datasets in end-diastolic (end-systolic) phase demonstrates accuracy and robustness, with 2.45 mm (2.84 mm) mean deviation from manual segmentation.}, address = {Philips Research Laboratories, Sector Technical Systems, R\"{o}ntgenstr. 24-26, D-22335 Hamburg, Germany. michael.kaus@philips.com}, author = {Kaus, M. R. and von Berg, J. and Weese, J. and Niessen, W. and Pekar, V.}, citeulike-article-id = {2494933}, citeulike-linkout-0 = {http://dx.doi.org/10.1016/j.media.2004.06.015}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/15450219}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=15450219}, citeulike-linkout-3 = {http://www.sciencedirect.com/science/article/B6W6Y-4D09D3J-1/1/e8711250757842edfb6da37c62d58386}, doi = {10.1016/j.media.2004.06.015}, issn = {1361-8415}, journal = {Med Image Anal}, keywords = {3d, cardiac, mri, segmentation}, month = {September}, number = {3}, pages = {245--254}, posted-at = {2008-09-10 18:32:29}, priority = {2}, title = {Automated segmentation of the left ventricle in cardiac MRI.}, url = {http://dx.doi.org/10.1016/j.media.2004.06.015}, volume = {8}, year = {2004} }

TY - JOUR ID - citeulike:2494933 L3 - citeulike-article-id:2494933 N2 - We present a fully automated deformable model technique for myocardium segmentation in 3D MRI. Loss of signal due to blood flow, partial volume effects and significant variation of surface grey value appearance make this a difficult problem. We integrate various sources of prior knowledge learned from annotated image data into a deformable model. Inter-individual shape variation is represented by a statistical point distribution model, and the spatial relationship of the epi- and endocardium is modeled by adapting two coupled triangular surface meshes. To robustly accommodate variation of grey value appearance around the myocardiac surface, a prior parametric spatially varying feature model is established by classification of grey value surface profiles. Quantitative validation of 121 3D MRI datasets in end-diastolic (end-systolic) phase demonstrates accuracy and robustness, with 2.45 mm (2.84 mm) mean deviation from manual segmentation. IS - 3 JF - Med Image Anal SN - 1361-8415 AD - Philips Research Laboratories, Sector Technical Systems, Röntgenstr. 24-26, D-22335 Hamburg, Germany. michael.kaus@philips.com EP - 254 TI - Automated segmentation of the left ventricle in cardiac MRI. VL - 8 SP - 245 KW - 3d KW - cardiac KW - mri KW - segmentation AU - Kaus, MR AU - von Berg, J AU - Weese, J AU - Niessen, W AU - Pekar, V PY - 2004/09// UR - http://dx.doi.org/10.1016/j.media.2004.06.015 ER -