NeuroMem®芯片用于乳腺癌检测的低成本乳房x光片分割和分类

2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI) Pub Date : 2023-08-01 DOI:10.1109/IRI58017.2023.00054

Soumeya Demil, Lydia Bouzar-Benlabiod, G. Paillet

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引用次数: 0

摘要

本文提出了一种计算机辅助诊断系统来检测和分类乳房x线照片上的异常。本文提出了一种基于NeuroMem®芯片NM500的异常提取分割方法，该方法集成了物理神经网络，可检测到高达83%的异常。我们为乳房x线照片的分类步骤配置了两个子网，准确率达到87%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Cost Efficient Mammogram Segmentation and Classification with NeuroMem® Chip for Breast Cancer Detection

In this paper, a Computer Aided Diagnosis system to detect and classify anomalies on mammograms is proposed. A segmentation method for anomaly extraction has been proposed using the NeuroMem® Chip NM500 which integrates physical neural networks, up to 83% of the anomalies were detected. We configured two subnetworks for the mammogram classification step the accuracy reached 87%.

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来源期刊

2023 IEEE 24th International Conference on Information Reuse and Integration for Data Science (IRI)

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