TY - GEN
T1 - 3D automatic approach for precise segmentation of the prostate from diffusion-weighted magnetic resonance imaging
AU - Firjani, A.
AU - Khalifa, F.
AU - Elnakib, A.
AU - Gimel'farb, G.
AU - El-Ghar, M. Abo
AU - Elmaghraby, A.
AU - El-Baz, A.
PY - 2011
Y1 - 2011
N2 - Prostate segmentation is an essential step in developing any non-invasive Computer-Assisted Diagnostic (CAD) system for the early diagnosis of prostate cancer using Magnetic Resonance Images (MRI). In this paper, a novel framework for 3D segmentation of the prostate region from Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is proposed. The framework is based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for Markov-Gibbs shape and appearance models of the object-of-interest and its background. The framework was evaluated on in vivo prostate DW-MRI with available manual expert segmentation. The performance evaluation of the proposed segmentation approach, based on voxel-based and distance-based metrics between manually drawn and automatically segmented contours, confirmed the robustness and accuracy of the proposed segmentation approach.
AB - Prostate segmentation is an essential step in developing any non-invasive Computer-Assisted Diagnostic (CAD) system for the early diagnosis of prostate cancer using Magnetic Resonance Images (MRI). In this paper, a novel framework for 3D segmentation of the prostate region from Diffusion-Weighted Magnetic Resonance Imaging (DW-MRI) is proposed. The framework is based on a Maximum A Posteriori (MAP) estimate of a new log-likelihood function that accounts for Markov-Gibbs shape and appearance models of the object-of-interest and its background. The framework was evaluated on in vivo prostate DW-MRI with available manual expert segmentation. The performance evaluation of the proposed segmentation approach, based on voxel-based and distance-based metrics between manually drawn and automatically segmented contours, confirmed the robustness and accuracy of the proposed segmentation approach.
UR - http://www.scopus.com/inward/record.url?scp=84856254693&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84856254693&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2011.6116095
DO - 10.1109/ICIP.2011.6116095
M3 - Conference contribution
AN - SCOPUS:84856254693
SN - 9781457713033
T3 - Proceedings - International Conference on Image Processing, ICIP
SP - 2285
EP - 2288
BT - ICIP 2011
T2 - 2011 18th IEEE International Conference on Image Processing, ICIP 2011
Y2 - 11 September 2011 through 14 September 2011
ER -
