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讨好美人

Varifold-Based Matching of Curves via Sobolev-Type Riemannian Metricsching to explore a new strategy of computing geodesics between unparametrized curves. We describe the numerical method used for solving the inexact matching problem, apply it to study the shape of mosquito wings and compare our method to curve matching in the LDDMM framework.

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Efficient Parallel Transport in the Group of Diffeomorphisms via Reduction to the Lie Algebraroaches to parallel transport in large deformation diffeomorphic metric mapping (LDDMM) of images represent a momenta field, the dual of a tangent vector to the diffeomorphism group, as a scalar field times the image gradient. This “scalar momenta” constraint couples tangent vectors with the images

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Srdan Verstovsek,Ayalew Tefferi of cortical brain regions capture information about the structure of connections in the entire network. Hence, anatomical changes in network connectivity (e.g., caused by a certain disease) should translate into changes in the community structure of brain regions. This means that essential structur

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https://doi.org/10.1007/978-3-662-65075-2h. Much work has therefore been done investigating the use of machine-learning techniques on functional and structural connectivity networks for ASD diagnosis. However, networks based on the morphology of the brain have yet to be similarly investigated, despite research findings that morphological f

DEI

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https://doi.org/10.1007/978-3-642-87074-3pproaches to analyze skin images. In order to explore and gain insights into datasets of skin images, we propose a graph based approach to visualize a progression of similar skin images between pairs of images. In our graph, a node represents both a clinical and dermoscopic image of the same lesion,

FID

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