Helping Breast Cancer Diagnosis on Mammographies using Convolutional Neural Networks

Rocío García-Mojón, Fernando Martín-Rodríguez, Mónica Fernández-Barciela
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Abstract

In this paper a study about breast cancer detection is presented. Mammography images in DICOM format are processed using Convolutional Neural Networks (CNNs) to get a pre-diagnosis. Of course, this preliminary result needs to be checked by a trained radiologist. CNNs are trained and checked using a big database that is publicly available. Standard measurements for success are computed (accuracy, precision, recall) obtaining outstanding results better than other examples from the literature.
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利用卷积神经网络帮助乳房X光片诊断乳腺癌
本文介绍了一项关于乳腺癌检测的研究。使用卷积神经网络 (CNN) 处理 DICOM 格式的乳腺 X 射线图像,以获得预诊断结果。当然,这一初步结果需要由训练有素的放射科医生进行检查。CNN 通过一个公开的大型数据库进行训练和检查。通过计算成功的标准衡量标准(准确度、精确度、召回率),获得了优于其他文献实例的出色结果。
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