Classification of Breast Abnormalities Using Deep Learning

被引：4
|
作者：
Gomina, P. S. [1 ]
Kober, V. I. [1 ,2 ,4 ]
Karnaukhov, V. N. [2 ]
Mozerov, M. G. [2 ]
Kober, A. V. [3 ]
机构：
[1] Chelyabinsk State Univ, Chelyabinsk 454001, Russia
[2] Russian Acad Sci, Kharkevich Inst Informat Transmiss Problems, Moscow 127051, Russia
[3] Russian Acad Sci, Fed Res Ctr Biol Syst & Agrotechnol, Orenburg 460000, Russia
[4] Ctr Sci Res & Higher Educ, Ensenada 22860, Baja California, 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：
on; digital mammography; U-net deep convolutional neural network; data augmentation; RECOGNITION; DIAGNOSIS;
D O I：
10.1134/S1064226922120051
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：
Early detection of breast abnormalities through mammography screening and proper treatment reduces mortality and increases women's life expectancy. Currently, methods and algorithms for computer diagnostic systems based on deep neural networks are being actively developed. Such systems combine selection, feature calculation, and classification, thereby directly creating a decision-making function. In this paper, a method for classifying breast pathologies according to the Breast Imaging Reporting and Data System (BI-RADS) based on deep learning is proposed. Experimental results are presented using two open databases of digital mammography and evaluated using various performance criteria.
引用
收藏
页码：1552 / 1556
页数：5
相关论文
共 50 条
  • [21] Classification of Metastatic Breast Cancer Cell using Deep Learning Approach
    Lee, Seohyun
    Kim, Hyuno
    Higuchi, Hideo
    Ishikawa, Masatoshi
    3RD INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE IN INFORMATION AND COMMUNICATION (IEEE ICAIIC 2021), 2021, : 425 - 428
  • [22] Segmentation and classification of breast cancer using novel deep learning architecture
    Ramesh, S.
    Sasikala, S.
    Gomathi, S.
    Geetha, V
    Anbumani, V
    NEURAL COMPUTING & APPLICATIONS, 2022, 34 (19): : 16533 - 16545
  • [23] Breast Cancer Classification Using Discrete Wavelet Transformation and Deep Learning
    Masa-Ibi E.
    Prasad R.
    Recent Advances in Computer Science and Communications, 2021, 14 (07) : 2103 - 2112
  • [24] Automatic breast cancer detection and classification using deep learning techniques
    Lakshmi Prasanna, K.
    Ashwini, S.
    Test Engineering and Management, 2019, 81 (11-12): : 5505 - 5510
  • [25] Fully Automated Breast Density Segmentation and Classification Using Deep Learning
    Saffari, Nasibeh
    Rashwan, Hatem A.
    Abdel-Nasser, Mohamed
    Kumar Singh, Vivek
    Arenas, Meritxell
    Mangina, Eleni
    Herrera, Blas
    Puig, Domenec
    DIAGNOSTICS, 2020, 10 (11)
  • [26] Segmentation and classification of breast cancer using novel deep learning architecture
    S. Ramesh
    S. Sasikala
    S. Gomathi
    V. Geetha
    V. Anbumani
    Neural Computing and Applications, 2022, 34 : 16533 - 16545
  • [27] A Deep Learning Based Breast Cancer Classification System Using Mammograms
    G. Meenalochini
    S. Ramkumar
    Journal of Electrical Engineering & Technology, 2024, 19 : 2637 - 2650
  • [28] Classification of Multiclass Histopathological Breast Images Using Residual Deep Learning
    Eltoukhy, Mohamed Meselhy
    Hosny, Khalid M.
    Kassem, Mohamed A.
    COMPUTATIONAL INTELLIGENCE AND NEUROSCIENCE, 2022, 2022
  • [29] Breast Cancer Detection and Classification using Deep Learning Xception Algorithm
    Abunasser, Basem S.
    AL-Hiealy, Mohammed Rasheed J.
    Zaqout, Ihab S.
    Abu-Naser, Samy S.
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2022, 13 (07) : 223 - 228
  • [30] CLASSIFICATION OF BREAST LESIONS USING CROSS-MODAL DEEP LEARNING
    Hadad, Omer
    Bakalo, Ran
    Ben-Ari, Rami
    Hashoul, Sharbell
    Amit, Guy
    2017 IEEE 14TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2017), 2017, : 109 - 112
12345