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- W1605843559 abstract "This paper reports our methodology and initial results on volumetric pathological neuroimage retrieval. A set of novel image features are computed to quantify the statistical distributions of approximate bilateral asymmetry of normal and pathological human brains. We apply memory-based learning method to find the most-discriminative feature subset through image classification according to predefined semantic categories. Finally, this selected feature subset is used as indexing features to retrieve medically similar images under a semantic-based image retrieval framework. Quantitative evaluations are provided." @default.
- W1605843559 created "2016-06-24" @default.
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- W1605843559 date "2001-01-01" @default.
- W1605843559 modified "2023-09-24" @default.
- W1605843559 title "Classification-Driven Pathological Neuroimage Retrieval Using Statistical Asymmetry Measures" @default.
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- W1605843559 doi "https://doi.org/10.1007/3-540-45468-3_79" @default.
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