A Review of Artificial Intelligence in Breast Imaging.

Journal: Tomography (Ann Arbor, Mich.)
Published Date:

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.

Authors

  • Dhurgham Al-Karawi
    Medical Analytica Ltd, Flintshire, UK.
  • Shakir Al-Zaidi
    Medical Analytica Ltd., 26a Castle Park Industrial Park, Flint CH6 5XA, UK.
  • Khaled Ahmad Helael
    Royal Medical Services, King Hussein Medical Hospital, King Abdullah II Ben Al-Hussein Street, Amman 11855, Jordan.
  • Naser Obeidat
    Department of Diagnostic Radiology and Nuclear Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
  • Abdulmajeed Mounzer Mouhsen
    Department of Diagnostic Radiology and Nuclear Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
  • Tarek Ajam
    Department of Diagnostic Radiology and Nuclear Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
  • Bashar A Alshalabi
    Department of Diagnostic Radiology and Nuclear Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
  • Mohamed Salman
    Department of Diagnostic Radiology and Nuclear Medicine, Faculty of Medicine, Jordan University of Science and Technology, Irbid 22110, Jordan.
  • Mohammed H Ahmed
    School of Computing, Coventry University, 3 Gulson Road, Coventry CV1 5FB, UK.