Robust Computation of Mutual Information Using Spatially Adaptive Meshes [chapter]

Hari Sundar, Dinggang Shen, George Biros, Chenyang Xu, Christos Davatzikos
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2007  
We present a new method for the fast and robust computation of information theoretic similarity measures for alignment of multi-modality medical images. The proposed method defines a non-uniform, adaptive sampling scheme for estimating the entropies of the images, which is less vulnerable to local maxima as compared to uniform and random sampling. The sampling is defined using an octree partition of the template image, and is preferable over other proposed methods of non-uniform sampling since
more » ... t respects the underlying data distribution. It also extends naturally to a multi-resolution registration approach, which is commonly employed in the alignment of medical images. The effectiveness of the proposed method is demonstrated using both simulated MR images obtained from the BrainWeb database and clinical CT and SPECT images. N. Ayache, S. Ourselin, A. Maeder (Eds.): MICCAI 2007, Part I, LNCS 4791, pp. 950-958, 2007.
doi:10.1007/978-3-540-75757-3_115 dblp:conf/miccai/SundarSBXD07 fatcat:7dopyvagcrbrjprlf7yimi4tei