Segmentation of Breast Masses in Digital Mammography Based on U-Net Deep Convolutional Neural Networks

被引：0

作者：

A. N. Ruchay

V. I. Kober

K. A. Dorofeev

V. N. Karnaukhov

M. G. Mozerov

机构：

[1] Chelyabinsk State University,

[2] Kharkevich Institute for Information Transmission Problems,undefined

[3] Russian Academy of Sciences,undefined

[4] South Ural State University (National Research University),undefined

[5] Center of Scientific Research and Higher Education,undefined

来源：

Journal of Communications Technology and Electronics | 2022年 / 67卷

关键词：

segmentation; digital mammography; U-Net deep convolutional neural network; data augmentation;

D O I：

暂无

中图分类号：

学科分类号：

摘要：

In this paper, we propose a new algorithm for segmentation of breast masses in digital mammography based on U-Net deep convolutional neural networks. All raw mammogram images are preprocessed to improve segmentation reliability. Deep learning was carried out using additional methods of data augmentation and fine tuning of the neural network. The performance of the proposed algorithm for segmentation of breast masses using the known CBIS-DDSM database is discussed.

引用

页码：1531 / 1541

页数：10

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