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Current Medical Imaging

Editor-in-Chief

ISSN (Print): 1573-4056
ISSN (Online): 1875-6603

Review Article

Breast Cancer Image Classification: A Review

Author(s): Pooja Pathak, Anand Singh Jalal* and Ritu Rai

Volume 17 , Issue 6 , 2021

Published on: 28 December, 2020

Page: [720 - 740] Pages: 21

DOI: 10.2174/0929867328666201228125208

Price: $65

Abstract

Background: Breast cancer represents uncontrolled breast cell growth. Breast cancer is the most diagnosed cancer in women worldwide. Early detection of breast cancer improves the chances of survival and increases treatment options. There are various methods for screening breast cancer, such as mammogram, ultrasound, computed tomography and Magnetic Resonance Imaging (MRI). MRI is gaining prominence as an alternative screening tool for early detection and breast cancer diagnosis. Nevertheless, MRI can hardly be examined without the use of a Computer-Aided Diagnosis (CAD) framework, due to the vast amount of data.

Objective: This paper aims to cover the approaches used in the CAD system for the detection of breast cancer.

Methods: In this paper, the methods used in CAD systems are categories into two classes: the conventional approach and artificial intelligence (AI) approach.

Results: The conventional approach covers the basic steps of image processing, such as preprocessing, segmentation, feature extraction and classification. The AI approach covers the various convolutional and deep learning networks used for diagnosis.

Conclusion: This review discusses some of the core concepts used in breast cancer and presents a comprehensive review of efforts in the past to address this problem.

Keywords: Breast cancer, Computer-Aided Diagnosis (CAD), artificial intelligence, tumour, medical imaging, image classification.

Graphical Abstract
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