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Lecture Notes in Computer Science
This paper advocates a novel material-aware feature descriptor for volumetric image registration. We rigorously formulate a novel probability density function (PDF) based distance metric to devise a compact local feature descriptor supporting invariance of full 3D orientation and isometric deformation. The central idea is to employ anisotropic heat diffusion to characterize the detected local volumetric features. It is achieved by the elegant unification of diffusion tensor (DT) spacedoi:10.1007/978-3-642-33765-9_36 fatcat:vydmziiumneuzgnzdf46o22nwy