Large Margin Aggregation of Local Estimates for Medical Image Classification

Abstract

Medical images typically exhibit complex feature space distributions due to high intra-class variation and inter-class ambiguity. Monolithic classification models are often problematic. In this study, we propose a novel Large Margin Local Estimate (LMLE) method for medical image classification. In the first step, the reference images are subcategorized, and… (More)
DOI: 10.1007/978-3-319-10470-6_25

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@article{Song2014LargeMA, title={Large Margin Aggregation of Local Estimates for Medical Image Classification}, author={Yang Song and Tom Weidong Cai and Heng Huang and Yun Zhou and David Dagan Feng and Mei Chen}, journal={Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention}, year={2014}, volume={17 Pt 2}, pages={196-203} }