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Computer Aided Detection and Diagnosis System for Breast Cancer Detection Based on High Resolution 3D micro-CT Breast Microcalcifications Authors: R. Brahimetaj, E. Papavasileiou, F. Temmermans, B. Cornelis, I. Willekens, J. De Mey and B. Jansen Publication Year: 2019
Abstract: In this study we propose a Computer Aided Detection and Diagnosis System to detect breast cancer based on characteristics of individual microcalcifications (main indicators of an early breast cancer) by scanning breast tissue with micro-CT, a high resolution 3D imaging modality. By integrating supervised machine learning techniques with feature extraction and feature selection methods, we are able to classify MCs as benign or malignant with 75.88% accuracy, 62.13% sensitivity and 86.39% specificity, outperforming the state of the art.
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