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Artificial intelligence methods for the diagnosis of breast cancer by image processing: a review

Authors Sadoughi F, Kazemy Z, Hamedan F, Owji L, Rahmanikatigari M, Talebi Azadboni T

Received 25 May 2018

Accepted for publication 26 September 2018

Published 30 November 2018 Volume 2018:10 Pages 219—230

DOI https://doi.org/10.2147/BCTT.S175311

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Colin Mak

Peer reviewer comments 2

Editor who approved publication: Professor Pranela Rameshwar


Farahnaz Sadoughi,1 Zahra Kazemy,1 Farahnaz Hamedan,1 Leila Owji,1 Meysam Rahmanikatigari,2 Tahere Talebi Azadboni1

1Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran; 2Social Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran

Abstract: Breast cancer is the most common cancer among women around the world. Despite enormous medical progress, breast cancer has still remained the second leading cause of death worldwide; thus, its early diagnosis has a significant impact on reducing mortality. However, it is often difficult to diagnose breast abnormalities. Different tools such as mammography, ultrasound, and thermography have been developed to screen breast cancer. In this way, the computer helps radiologists identify chest abnormalities more efficiently using image processing and artificial intelligence (AI) tools. This article examined various methods of AI using image processing to diagnose breast cancer. It was a review study through library and Internet searches. By searching the databases such as Medical Literature Analysis and Retrieval System Online (MEDLINE) via PubMed, Springer, IEEE, ScienceDirect, and Gray Literature (including Google Scholar, articles published in conferences, government technical reports, and other materials not controlled by scientific publishers) and searching for breast cancer keywords, AI and medical image processing techniques were extracted. The results were provided in tables to demonstrate different techniques and their results over recent years. In this study, 18,651 articles were extracted from 2007 to 2017. Among them, those that used similar techniques and reported similar results were excluded and 40 articles were finally examined. Since each of the articles used image processing, a list of features related to the image used in each article was also provided. The results showed that support vector machines had the highest accuracy percentage for different types of images (ultrasound =95.85%, mammography =93.069%, thermography =100%). Computerized diagnosis of breast cancer has greatly contributed to the development of medicine, is constantly being used by radiologists, and is clear in ethical and medical fields with regard to its effects. Computer-assisted methods increase diagnosis accuracy by reducing false positives.

Keywords: breast cancer, breast cancer screening techniques, artificial intelligence techniques, medical image processing

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