A Weighted Multi-Sequence Markov Model For Brain Lesion Segmentation
作者： Michel Dojat , Senan Doyle , Christian Barillot , Florence Forbes , Daniel García-Lorenzo
DOI:
关键词: Hidden Markov model 、 Task (project management) 、 Artificial intelligence 、 Sequence 、 Pattern recognition 、 A-weighting 、 A priori and a posteriori 、 Brain lesions 、 Markov model 、 Computer science 、 Segmentation
摘要: We propose a technique for fusing the output of multiple Magnetic Resonance (MR) sequences to robustly and accurately segment brain lesions. It is based on an augmented multi-sequence hidden Markov model that includes additional weight variables account relative importance control impact each sequence. The framework has advantage allowing 1) incorporation expert knowledge priori relevant information content sequence 2) weighting scheme which modied adaptively according data segmentation task under consideration. model, applied detection sclerosis stroke lesions shows promising results.
参考文章(23)
Charles Kervrann, Pierre Yger, Pierrick Coupé, Campus de Beaulieu, Sylvain Prima, Christian Barillot, Pierre Hellier, An Optimized Blockwise Non Local Means Denoising Filter for 3D Magnetic Resonance Images ,(2007)
Julian Besag, On the statistical analysis of dirty pictures Journal of the royal statistical society series b-methodological. ,vol. 48, pp. 259- 279 ,(1986) , 10.1111/J.2517-6161.1986.TB01412.X
JM Bernardo, MJ Bayarri, JO Berger, AP Dawid, D Heckerman, AFM Smith, M West, The variational Bayesian EM algorithm for incomplete data: with application to scoring graphical model structures Oxford University Press. ,(2003)
J McLachlan, G, D. Peel, Finite Mixture Models ,(2000)
Benoit Scherrer, Florence Forbes, Catherine Garbay, Michel Dojat, Fully Bayesian Joint Model for MR Brain Scan Tissue and Structure Segmentation medical image computing and computer assisted intervention. ,vol. 5242, pp. 1066- 1074 ,(2008) , 10.1007/978-3-540-85990-1_128
Lee R. Dice, Measures of the Amount of Ecologic Association Between Species Ecology. ,vol. 26, pp. 297- 302 ,(1945) , 10.2307/1932409
Aki Vehtari, David B. Dunson, Andrew Gelman, Hal S. Stern, Donald B. Rubin, John B. Carlin, Bayesian Data Analysis ,(1995)
Balasrinivasa Rao Sajja, Sushmita Datta, Renjie He, Meghana Mehta, Rakesh K. Gupta, Jerry S. Wolinsky, Ponnada A. Narayana, Unified approach for multiple sclerosis lesion segmentation on brain MRI. Annals of Biomedical Engineering. ,vol. 34, pp. 142- 151 ,(2006) , 10.1007/S10439-005-9009-0
A. P. Dempster, N. M. Laird, D. B. Rubin, Maximum Likelihood from Incomplete Data Via theEMAlgorithm Journal of the Royal Statistical Society: Series B (Methodological). ,vol. 39, pp. 1- 22 ,(1977) , 10.1111/J.2517-6161.1977.TB01600.X
Gilles Celeux, Florence Forbes, Nathalie Peyrard, EM Procedures Using Mean Field-Like Approximations for Markov Model-Based Image Segmentation Pattern Recognition. ,vol. 36, pp. 131- 144 ,(2003) , 10.1016/S0031-3203(02)00027-4