Evidential segmentation scheme of multi-echo MR images for the detection of brain tumors using neighborhood information

Abstract

In this paper we propose and study an evidential segmentation scheme of multi-echo MR images for the detection of brain tumors. We show that the modeling by means of evidence theory is well suited to the processing of redundant and complementary data as the MR images. Moreover neighborhood relationship between voxels is taken into account via Dempster's combination rule. We show that using this information improves the classification results previously obtained and leads to a real region-based segmentation. Moreover, the combination of spatial information allows to compute a measure of conflict, which reflects the spatial organization of the data: the conflict is higher at the boundaries between different structures. Thus, it provides a new source of evidence that the specialist can aggregate with the segmentation results to soften its own decision.