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Mammographic image segmentation and risk classification based on mammographic parenchymal patterns and geometric moments.

, , , and . Biomed. Signal Process. Control., 6 (3): 321-329 (2011)

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Modelling Breast Tissue in Mammograms for Mammographic Risk Assessment., , and . MIUA, page 37-42. BMVA, (2011)A review of automatic mass detection and segmentation in mammographic images., , , , , , and . Medical Image Anal., 14 (2): 87-110 (2010)Bag of visual words based approach for the classification of benign and malignant masses in mammograms using voting-based feature encoding., , , and . IWBI, volume 10718 of SPIE Proceedings, page 107181A. SPIE, (2018)Breast image pre-processing for mammographic tissue segmentation., , , , and . Comput. Biol. Medicine, (2015)End-to-end breast ultrasound lesions recognition with a deep learning approach., , , , , , , and . Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging, volume 10578 of SPIE Proceedings, page 1057819. SPIE, (2018)Topographic representation based breast density segmentation for mammographic risk assessment., , and . ICIP, page 1993-1996. IEEE, (2012)Voxel Similarity Measures for 3D Serial MR Brain Image Registration., , , , , , , and . IEEE Trans. Med. Imaging, 19 (2): 94-102 (2000)Automatic Segmentation of Microcalcification Clusters., , , and . MIUA, volume 894 of Communications in Computer and Information Science, page 251-261. Springer, (2018)A Revisit on Correlation between Tabár and Birads Based Risk Assessment Schemes with Full Field Digital Mammography., , , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 327-333. Springer, (2014)A Novel Image Enhancement Methodology for Full Field Digital Mammography., , , , , and . Digital Mammography / IWDM, volume 8539 of Lecture Notes in Computer Science, page 650-657. Springer, (2014)