TY - GEN
T1 - A new framework for automated identification of pathological tissues in contrast enhanced cardiac magnetic resonance images
AU - Elnakib, Ahmed
AU - Beache, Garth M.
AU - Nitzken, M.
AU - Gimel'Farb, Georgy
AU - El-Baz, Ayman
PY - 2011
Y1 - 2011
N2 - A novel automated framework for quantification of myocardial viability in contrast enhanced cardiac magnetic resonance images (CE-CMRI) is proposed. The framework consists of three main steps. First, the inner and outer borders of the left ventricle (LV) wall (myocardium wall) are segmented from the surrounding tissue. Second, the pathological tissue in the myocardium wall is identified using a MAP-based classifier based on the visual appearance and spatial interaction of the LV pathological tissue as well as healthy tissue. Third, the myocardial viability is assessed and quantified based on measuring two parameters: the percentage of pathological tissue with respect to the area of the myocardium wall and the transmural extent of the pathological tissue in the myocardium wall. The transmural extent is estimated based on a new Partial Differential Equation (PDE) approach to determine point-to-point correspondences between the inner and outer borders of the pathological area as well as the myocardium wall. The proposed framework was tested on in-vivo CE-CMR images and validated with manual expert delineations of pathological tissue. Experiments and comparison results on real CE-CMR images confirm the robustness and accuracy of the proposed framework over the existing ones.
AB - A novel automated framework for quantification of myocardial viability in contrast enhanced cardiac magnetic resonance images (CE-CMRI) is proposed. The framework consists of three main steps. First, the inner and outer borders of the left ventricle (LV) wall (myocardium wall) are segmented from the surrounding tissue. Second, the pathological tissue in the myocardium wall is identified using a MAP-based classifier based on the visual appearance and spatial interaction of the LV pathological tissue as well as healthy tissue. Third, the myocardial viability is assessed and quantified based on measuring two parameters: the percentage of pathological tissue with respect to the area of the myocardium wall and the transmural extent of the pathological tissue in the myocardium wall. The transmural extent is estimated based on a new Partial Differential Equation (PDE) approach to determine point-to-point correspondences between the inner and outer borders of the pathological area as well as the myocardium wall. The proposed framework was tested on in-vivo CE-CMR images and validated with manual expert delineations of pathological tissue. Experiments and comparison results on real CE-CMR images confirm the robustness and accuracy of the proposed framework over the existing ones.
UR - http://www.scopus.com/inward/record.url?scp=80055056482&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=80055056482&partnerID=8YFLogxK
U2 - 10.1109/ISBI.2011.5872633
DO - 10.1109/ISBI.2011.5872633
M3 - Conference contribution
AN - SCOPUS:80055056482
SN - 9781424441280
T3 - Proceedings - International Symposium on Biomedical Imaging
SP - 1272
EP - 1275
BT - 2011 8th IEEE International Symposium on Biomedical Imaging
T2 - 2011 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI'11
Y2 - 30 March 2011 through 2 April 2011
ER -