Medical Analytica Ltd., 26a Castle Park Industrial Park, Flint CH6 5XA, UK.
Royal Medical Services, King Hussein Medical Hospital, King Abdullah II Ben Al-Hussein Street, Amman 11855, Jordan.
Tomography. 2024 May 9;10(5):705-726. doi: 10.3390/tomography10050055.
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.
随着人工智能(AI)技术的日益主导地位,其应用的重要前景已经扩展到各个医学领域,包括体外诊断、智能康复、医学成像和预后等领域。乳腺癌是一种常见的恶性肿瘤,严重影响着女性的身心健康。早期乳腺癌筛查——通过乳房 X 线摄影、超声或磁共振成像(MRI)——可以显著改善乳腺癌患者的预后。人工智能应用在各种图像识别任务中表现出色,并且已经在许多研究中探索了它们在乳腺癌筛查中的应用。本文介绍了相关的 AI 技术及其在乳腺医学成像(乳房 X 线摄影和超声)领域的应用,特别是在识别、分割和分类病变、评估乳腺癌风险以及提高图像质量方面。本文专注于乳腺癌的医学成像,还回顾了 AI 相关的挑战和前景。