Cortical Correspondence with Probabilistic Fiber Connectivity

TitleCortical Correspondence with Probabilistic Fiber Connectivity
Publication TypeConference Paper
Year of Publication2009
AuthorsOguz I, Niethammer M, Cates J, Whitaker R, Fletcher T, Styner M
Conference NameProceedings of the Conference on Information Processing in Medical Imaging (IPMI)

This paper presents a novel method of optimizing pointbased correspondence among populations of human cortical surfaces by combining structural cues with probabilistic connectivity maps. The proposed method establishes a tradeo between an even sampling of the cortical surfaces (a low surface entropy) and the similarity of corresponding points across the population (a low ensemble entropy). The similarity metric, however, isn't constrained to be just spatial proximity, but uses local sulcal depth measurements as well as probabilistic connectivity maps, computed from DWI scans via a stochastic tractography algorithm, to enhance the correspondence denition. We propose a novel method for projecting this ber connectivity information on the cortical surface, using a surface evolution technique. Our cortical correspondence method does not require a spherical parameterization. Experimental results are presented, showing improved correspondence quality demonstrated by a cortical thickness analysis, as compared to correspondence methods using spatial metrics as the sole correspondence criterion.