A Review of Artificial Intelligence in Breast Imaging.
artificial intelligence network
breast cancer
deep learning
machine learning
mammography image
ultrasound image
Journal
Tomography (Ann Arbor, Mich.)
ISSN: 2379-139X
Titre abrégé: Tomography
Pays: Switzerland
ID NLM: 101671170
Informations de publication
Date de publication:
09 May 2024
09 May 2024
Historique:
received:
05
03
2024
revised:
14
04
2024
accepted:
06
05
2024
medline:
24
5
2024
pubmed:
24
5
2024
entrez:
24
5
2024
Statut:
epublish
Résumé
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.
Identifiants
pubmed: 38787015
pii: tomography10050055
doi: 10.3390/tomography10050055
doi:
Types de publication
Journal Article
Review
Langues
eng
Sous-ensembles de citation
IM