"Segmentation of the Prostate in MR images by Atlas Matching using Localised Mutual Information"
Stefan Klein, Uulke A. van der Heide, Marius Staring, Alexis N.T.J. Kotte, Bas W. Raaymakers and Josien P.W. Pluim
In this paper, an automatic method for delineating the prostate in MR scans is presented. The method is based on nonrigid registration of a set of prelabelled atlas images. Each atlas image is nonrigidly registered with the target patient image. After that, atlas images that match well to the patient image are selected and the segmentation is obtained by a majority voting rule. Two registration methods are investigated. The first one uses the common mutual information as a similarity measure. The second one uses a localised version of mutual information. Experiments are performed on 38 MR images using a leave-one-out approach. The automatic segmentations are evaluated with manual segmentations by computing their overlap. The localised mutual information measure outperforms the commonly used global version and achieves a median Dice similarity coefficient of 0.82. The spatial distribution of the segmentation errors is visualised using a spherical coordinate mapping of the prostate boundary.