A Review of Artificial Intelligence in Breast Imaging

Dhurgham Al-Karawi, Shakir Al-Zaidi, Khaled Ahmad Helael, Naser Obeidat, Abdulmajeed Mounzer Mouhsen, Tarek Ajam, Bashar A. Alshalabi, Mohamed Salman, Mohammed H. Ahmed

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    Abstract

    With the increasing dominance of artificial intelligence (AI) techniques, the important prospects for their application have extended to various medical fields, including domains such as in vitro diagnosis, intelligent rehabilitation, medical imaging, and prognosis. Breast cancer is a common malignancy that critically affects women’s physical and mental health. Early breast cancer screening—through mammography, ultrasound, or magnetic resonance imaging (MRI)—can substantially improve the prognosis for breast cancer patients. AI applications have shown excellent performance in various image recognition tasks, and their use in breast cancer screening has been explored in numerous studies. This paper introduces relevant AI techniques and their applications in the field of medical imaging of the breast (mammography and ultrasound), specifically in terms of identifying, segmenting, and classifying lesions; assessing breast cancer risk; and improving image quality. Focusing on medical imaging for breast cancer, this paper also reviews related challenges and prospects for AI.
    Original languageEnglish
    Pages (from-to)705-726
    Number of pages22
    JournalTomography
    Volume10
    Issue number5
    Early online date9 May 2024
    DOIs
    Publication statusE-pub ahead of print - 9 May 2024

    Bibliographical note

    © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).

    Keywords

    • breast cancer
    • deep learning
    • ultrasound image
    • mammography image
    • machine learning
    • artificial intelligence network

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