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The classification of medical images is a critical step for imaging-based clinical decision support systems. Existing classification methods for X-ray images, however, generally represent the image using only local texture or generic image features (e.g. color or shape) derived from predefined feature spaces. This limits the ability to quantify the image characteristics using general data-derived...
The recognition of the staining patterns of Human Epithelial-2 (HEp-2) cells in indirect immunofluorescence (IIF) images is essential for the diagnosis of several autoimmune diseases. The main challenge is the extraction and selection of the optimal feature set that not only represents the cells' characteristics, but also distinguishes between the classes of cell images with similar appearances. In...
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