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Segmentation and Classification of Triple Negative Breast Cancers Using DCE-MRI., , , , , , , , , and 1 other author(s). ISBI, page 1227-1230. IEEE, (2009)Automated grading of breast cancer histopathology using spectral clusteringwith textural and architectural image features., , , , and . ISBI, page 496-499. IEEE, (2008)Automated gland and nuclei segmentation for grading of prostate and breast cancer histopathology., , , , , and . ISBI, page 284-287. IEEE, (2008)Spectral embedding based active contour (SEAC): application to breast lesion segmentation on DCE-MRI., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 7963 of SPIE Proceedings, page 796305. SPIE, (2011)Spectral embedding-based registration (SERg) for multimodal fusion of prostate histology and MRI., , , , , , , , , and . Medical Imaging: Image Processing, volume 9034 of SPIE Proceedings, page 90343P. SPIE, (2014)Computer-aided prognosis: Predicting patient and disease outcome via quantitative fusion of multi-scale, multi-modal data., , , , and . Comput. Medical Imaging Graph., 35 (7-8): 506-514 (2011)Textural Kinetics: A Novel Dynamic Contrast-Enhanced (DCE)-MRI Feature for Breast Lesion Classification., , , , , , , , , and . J. Digital Imaging, 24 (3): 446-463 (2011)Computer-aided prognosis: predicting patient and disease outcome via multi-modal image analysis., , , , and . ISBI, page 1415-1418. IEEE, (2010)Computerized Image-Based Detection and Grading of Lymphocytic Infiltration in HER2+ Breast Cancer Histopathology., , , , , , , and . IEEE Trans. Biomed. Eng., 57 (3): 642-653 (2010)Novel kinetic texture features for breast lesion classification on dynamic contrast enhanced (DCE) MRI., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 6915 of SPIE Proceedings, page 69152C. SPIE, (2008)