24 March 2014 A contour-based shape descriptor for biomedical image classification and retrieval
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Abstract
Contours, object blobs, and specific feature points are utilized to represent object shapes and extract shape descriptors that can then be used for object detection or image classification. In this research we develop a shape descriptor for biomedical image type (or, modality) classification. We adapt a feature extraction method used in optical character recognition (OCR) for character shape representation, and apply various image preprocessing methods to successfully adapt the method to our application. The proposed shape descriptor is applied to radiology images (e.g., MRI, CT, ultrasound, X-ray, etc.) to assess its usefulness for modality classification. In our experiment we compare our method with other visual descriptors such as CEDD, CLD, Tamura, and PHOG that extract color, texture, or shape information from images. The proposed method achieved the highest classification accuracy of 74.1% among all other individual descriptors in the test, and when combined with CSD (color structure descriptor) showed better performance (78.9%) than using the shape descriptor alone.
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Daekeun You, Daekeun You, Sameer Antani, Sameer Antani, Dina Demner-Fushman, Dina Demner-Fushman, George R. Thoma, George R. Thoma, } "A contour-based shape descriptor for biomedical image classification and retrieval", Proc. SPIE 9021, Document Recognition and Retrieval XXI, 90210L (24 March 2014); doi: 10.1117/12.2042526; https://doi.org/10.1117/12.2042526
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