Convolutional Neural Networks for the segmentation of microcalcification\n in Mammography Imaging

2018/09/11 by Gabriele Valvano, Gianmarco Santini, Valvano, Gabriele +11
Computer Science · Medicine · #AI in cancer detection #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #Medical Imaging Techniques and Applications #Radiomics and Machine Learning in Medical Imaging

paper · pdf · doi:10.48550/arxiv.1809.03788

openalex publication_date 2018/09/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Cluster of microcalcifications can be an early sign of breast cancer. In this\npaper we propose a novel approach based on convolutional neural networks for\nthe detection and segmentation of microcalcification clusters. In this work we\nused 283 mammograms to train and validate our model, obtaining an accuracy of\n98.22% in the detection of preliminary suspect regions and of 97.47% in the\nsegmentation task. Our results show how deep learning could be an effective\ntool to effectively support radiologists during mammograms examination.\n

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