A Review of AI Methods for the Diagnosis of Breast Cancer by Image Processing

Authors

  • Mansi Yadav  Research Scholar, SHEAT College of Engineering, Varanasi, India
  • Mr. Sarad Nigam  Professor, SHEAT College of Engineering, Varanasi, India

Keywords:

Breast Cancer, Breast Cancer Screening Techniques, Artificial Intelligence Techniques, Medical Image Processing

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. 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.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2023-10-30

Issue

Volume 10, Issue 5, September-October-2023

Section

Research Articles

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How to Cite

[1]
Mansi Yadav, Mr. Sarad Nigam "A Review of AI Methods for the Diagnosis of Breast Cancer by Image Processing" International Journal of Scientific Research in Science, Engineering and Technology (IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 10, Issue 5, pp.194-201, September-October-2023.