Hierarchical manifold learning.

Kanwal K Bhatia,Anil Rao,Anthony N Price,Robin Wolz,Jo Hajnal,Daniel Rueckert

MEDICAL IMAGE COMPUTING AND COMPUTER-ASSISTED INTERVENTION - MICCAI 2012, PT I（2012）

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摘要

We present a novel method of hierarchical manifold learning which aims to automatically discover regional variations within images. This involves constructing manifolds in a hierarchy of image patches of increasing granularity, while ensuring consistency between hierarchy levels. We demonstrate its utility in two very different settings: (1) to learn the regional correlations in motion within a sequence of time-resolved images of the thoracic cavity; (2) to find discriminative regions of 3D brain images in the classification of neurodegenerative disease,

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关键词

novel method,hierarchy level,brain image,different setting,hierarchical manifold learning,regional correlation,discriminative region,image patch,neurodegenerative disease,regional variation

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