학술논문
Adaptive weighted fusion of multiple MR sequences for brain lesion segmentation
Document Type
Conference
Author
Source
2010 IEEE International Symposium on Biomedical Imaging: From Nano to Macro Biomedical Imaging: From Nano to Macro, 2010 IEEE International Symposium on. :69-72 Apr, 2010
Subject
Language
ISSN
1945-7928
1945-8452
1945-8452
Abstract
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 a Bayesian multi-sequence Markov model that includes weight parameters to account for the relative importance and control the impact of each sequence. The Bayesian framework has the advantage of allowing 1) the incorporation of expert knowledge on the a priori relevant information content of each sequence and 2) a weighting scheme which is modified adaptively according to the data and the segmentation task under consideration. The model, applied to the detection of multiple sclerosis and stroke lesions shows promising results.