Segmentation of Breast Masses in Digital Mammography Based on U-Net Deep Convolutional Neural Networks-Reference-Cited by-同舟云学术

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

Published:2022-12 Issue:12 Volume:67 Page:1531-1541
ISSN:1064-2269
Container-title:Journal of Communications Technology and Electronics
language:en
Short-container-title:J. Commun. Technol. Electron.

Author:

Ruchay A. N.,Kober V. I.,Dorofeev K. A.,Karnaukhov V. N.,Mozerov M. G.

Publisher

Pleiades Publishing Ltd

Subject

Electrical and Electronic Engineering,Condensed Matter Physics,Radiation,Electronic, Optical and Magnetic Materials

Link

https://link.springer.com/content/pdf/10.1134/S106422692212018X.pdf

Reference22 articles.

1. R. Lee, F. Gimenez, A. Hoogi, et al., “A curated mammography data set for use in computer-aided detection and diagnosis research,” Sci. Data 4, 170177 (2017).

2. J. Diaz, V. Kober, V. Karnaukhov, and M. Mozerov, “Recognition of breast abnormalities using phase fea-tures,” J. Commun. Technol. Electron. 65, 1476–1483 (2020).

3. I. Lbachir, I. Daoudi, and S. Tallal, “Automatic computer-aided diagnosis system for mass detection and classification inmammography,” Multimed Tools Appl. 80, 9493–9525 (2021).

4. A. Ruchai, V. Kober, K. Dorofeev, et al., “Classification of breast abnormalities using a deep convolutional neural network and transfer learning,” J. Commun. Technol. Electron. 66, 778–783 (2021).

5. L. Ahmed, M. Iqbal, H. Aldabbas, and S. Saeed, “Images data practices for semantic segmentation of breast cancer using deep neural network,” J. Ambient Intell. & Human. Comput., No. 01, (2020).

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1. Computer Diagnostics of Mammograms Based on Features Extracted Using Deep Learning;Journal of Communications Technology and Electronics;2024-07-29

2. Development of Computer Vision, Image Processing, and Analysis at the Digital Optics Laboratory of the Institute for Information Transmission Problems of the Russian Academy of Sciences;Pattern Recognition and Image Analysis;2023-12

3. Comparative Analysis of Convolutional Neural Networks for Classification of Breast Abnormalities;Journal of Communications Technology and Electronics;2023-12

4. Breast abnormalities classification using deep learning feature extraction;Applications of Digital Image Processing XLVI;2023-10-04

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