Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

Yassin Nisreen I. R.; Omran Shaimaa; El Houby Enas M. F.; Allam Hemat

首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

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Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

机译：使用不同图像方式的乳腺癌计算机辅助诊断机器学习技术：系统评价

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Background and objective: The high incidence of breast cancer in women has increased significantly in the recent years. Physician experience of diagnosing and detecting breast cancer can be assisted by using some computerized features extraction and classification algorithms. This paper presents the conduction and results of a systematic review (SR) that aims to investigate the state of the art regarding the computer aided diagnosis/detection (CAD) systems for breast cancer.

机译：背景和目的：近年来，女性乳腺癌的发病率显着增加。通过使用一些计算机化功能提取和分类算法，可以帮助诊断和检测乳腺癌的医生体验。本文介绍了系统评价（SR）的传导和结果，旨在调查关于乳腺癌的计算机辅助诊断/检测（CAD）系统的技术技术。

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《Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice》 |2018年第2018期|共21页
作者
Yassin Nisreen I. R.; Omran Shaimaa; El Houby Enas M. F.; Allam Hemat;
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作者单位

Natl Res Ctr Engn Res Div Syst &

Informat Dept Cairo 12311 Egypt;

Natl Res Ctr Engn Res Div Syst &

Informat Dept Cairo 12311 Egypt;

Natl Res Ctr Engn Res Div Syst &

Informat Dept Cairo 12311 Egypt;

Natl Res Ctr Anaesthesia &

Pain Med Div Cairo 12311 Egypt;

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原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
Breast cancer; Medical image modality; Classification; Machine learning techniques; Computer-aided diagnosis;

机译：乳腺癌;医学图像模态;分类;机器学习技术;计算机辅助诊断;

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1. Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review [J] . Yassin Nisreen I. R., Omran Shaimaa, El Houby Enas M. F., Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice . 2018,第期

机译：使用不同图像方式的乳腺癌计算机辅助诊断机器学习技术：系统评价
2. Machine Learning Methods for Computer-Aided Breast Cancer Diagnosis Using Histopathology: A Narrative Review [J] . Saxena Shweta, Gyanchandani Manasi Journal of medical imaging and radiation sciences . 2020,第1期

机译：计算机辅助乳腺癌诊断机器学习方法使用组织病理学：叙述评论
3. A Computer Aided Diagnosis System for Lung Cancer based on Statistical and Machine Learning Techniques [J] . Hamada R. H. Al-Absi1, Brahim Belhaouari Samir2, Suziah Sulaiman1 Journal of Computers . 2014,第2期

机译：基于统计和机器学习技术的肺癌计算机辅助诊断系统
4. A Review on Recent Deep Learning-Based Computer-Aided Systems for Breast Cancer Diagnosis [C] . Ali I??n, ?erife Kaba, Ahmet ?lhan International Conference on Theory and Application of Fuzzy Systems and Soft Computing . 2021

机译：近期深层学习的计算机辅助系统进行乳腺癌诊断综述
5. Modular machine learning methods for computer-aided diagnosis of breast cancer. [D] . Markey, Mia Kathleen. 2002

机译：用于乳腺癌的计算机辅助诊断的模块化机器学习方法。
6. Implementing Multilabeling ADASYN and ReliefF Techniques for Classification of Breast Cancer Diagnostic through Machine Learning: Efficient Computer-Aided Diagnostic System [O] . Taha Muthar Khan, Shengjun Xu, Zullatun Gull Khan, 2021

机译：通过机器学习实施乳腺癌诊断分类的多标签Adasyn和Creieff技术：高效的计算机辅助诊断系统
7. Machine Learning Methods for Computer-Aided Breast Cancer Diagnosis Using Histopathology: A Narrative Review [O] . Shweta Saxena, Manasi Gyanchandani 2020

机译：计算机辅助乳腺癌诊断机器学习方法使用组织病理学：叙事评论
8. Modular Machine Learning Methods for Computer-Aided Diagnosis of Breast Cancer [R] . Jesneck, J. , Lo, J. 2005

机译：用于计算机辅助诊断乳腺癌的模块化机器学习方法

Machine learning techniques for breast cancer computer aided diagnosis using different image modalities: A systematic review

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