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Image registration between histology and magnetic resonance imaging (MRI) isa challenging task due to differences in structural content and contrast. Toothick and wide specimens cannot be processed all at once and must be cut intosmaller pieces. This dramatically increases the complexity of the problem,since each piece should be individually and manually pre-aligned. To the bestof our knowledge, no automatic method can reliably locate such piece of tissuewithin its respective whole in the MRI slice, and align it without any priorinformation. We propose here a novel automatic approach to the joint problem ofmultimodal registration between histology and MRI, when only a fraction oftissue is available from histology. The approach relies on the representationof images using their level lines so as to reach contrast invariance. Shapeelements obtained via the extraction of bitangents are encoded in aprojective-invariant manner, which permits the identification of common piecesof curves between two images. We evaluated the approach on human brainhistology and compared resulting alignments against manually annotated groundtruths. Considering the complexity of the brain folding patterns, preliminaryresults are promising and suggest the use of characteristic and meaningfulshape elements for improved robustness and efficiency.

Part-to-whole Registration of Histology and MRI using Shape Elements