The application of ultrasound artificial intelligence in the diagnosis of endometrial diseases: Current practice and future development.
Authors
Affiliations (5)
Affiliations (5)
- Key Laboratory of Medical Imaging Precision Theranostics and Radiation Protection, College of Hunan Province, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.
- Institute of Medical Imaging, Hengyang Medical School, University of South China, Hengyang, China.
- Department of Computer Science and Technology, University of South China, Hengyang, China.
- College of Mechanical Engineering, University of South China, Hengyang, China.
- Department of Medical Imaging, the Affiliated Changsha Central Hospital, Hengyang Medical School, University of South China, Changsha, China.
Abstract
Diagnosis and treatment of endometrial diseases are crucial for women's health. Over the past decade, ultrasound has emerged as a non-invasive, safe, and cost-effective imaging tool, significantly contributing to endometrial disease diagnosis and generating extensive datasets. The introduction of artificial intelligence has enabled the application of machine learning and deep learning to extract valuable information from these datasets, enhancing ultrasound diagnostic capabilities. This paper reviews the progress of artificial intelligence in ultrasound image analysis for endometrial diseases, focusing on applications in diagnosis, decision support, and prognosis analysis. We also summarize current research challenges and propose potential solutions and future directions to advance ultrasound artificial intelligence technology in endometrial disease diagnosis, ultimately improving women's health through digital tools.