Artificial Intelligence in Obstetric and Gynecological MR Imaging.
Authors
Affiliations (3)
Affiliations (3)
- Department of Diagnostic and Interventional Radiology, Institute of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan.
- Department of Diagnostic and Interventional Radiology, University of Tsukuba Hospital, Tsukuba, Ibaraki, Japan.
- Department of Obstetrics and Gynecology, Institute of Medicine, University of Tsukuba, Tsukuba, Ibaraki, Japan.
Abstract
This review explores the significant progress and applications of artificial intelligence (AI) in obstetrics and gynecological MRI, charting its development from foundational algorithmic techniques to deep learning strategies and advanced radiomics. This review features research published over the last few years that has used AI with MRI to identify specific conditions such as uterine leiomyosarcoma, endometrial cancer, cervical cancer, ovarian tumors, and placenta accreta. In addition, it covers studies on the application of AI for segmentation and quality improvement in obstetrics and gynecology MRI. The review also outlines the existing challenges and envisions future directions for AI research in this domain. The growing accessibility of extensive datasets across various institutions and the application of multiparametric MRI are significantly enhancing the accuracy and adaptability of AI. This progress has the potential to enable more accurate and efficient diagnosis, offering opportunities for personalized medicine in the field of obstetrics and gynecology.