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

被引：6

作者：

Ruchay, A. N. ^{[1
,3
]}

Kober, V. I. ^{[1
,2
,4
]}

Dorofeev, K. A. ^{[1
]}

Karnaukhov, V. N. ^{[2
]}

Mozerov, M. G. ^{[2
]}

机构：

[1] Chelyabinsk State Univ, Chelyabinsk 454001, Russia

[2] Russian Acad Sci, Kharkevich Inst Informat Transmiss Problems, Moscow 127051, Russia

[3] South Ural State Univ, Natl Res Univ, Chelyabinsk 454080, Russia

[4] Ctr Sci Res & Higher Educ, Ensenada 22860, Mexico

来源：

JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS | 2022年 / 67卷 / 12期

基金：

俄罗斯科学基金会;

关键词：

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

D O I：

10.1134/S106422692212018X

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

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：11

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