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人工智能在妇产科磁共振成像中的应用

Artificial Intelligence in Obstetric and Gynecological MR Imaging.

作者信息

Saida Tsukasa, Gu Wenchao, Hoshiai Sodai, Ishiguro Toshitaka, Sakai Masafumi, Amano Taishi, Nakahashi Yuta, Shikama Ayumi, Satoh Toyomi, Nakajima Takahito

机构信息

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.

出版信息

Magn Reson Med Sci. 2024 Oct 29. doi: 10.2463/mrms.rev.2024-0077.

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.

摘要

本综述探讨了人工智能(AI)在妇产科磁共振成像(MRI)中的重大进展及应用,梳理了其从基础算法技术到深度学习策略以及先进的放射组学的发展历程。本综述重点介绍了过去几年发表的研究,这些研究利用AI与MRI来识别特定病症,如子宫平滑肌肉瘤、子宫内膜癌、宫颈癌、卵巢肿瘤和胎盘植入。此外,还涵盖了关于AI在妇产科MRI分割和质量改进方面应用的研究。该综述还概述了现有挑战,并展望了该领域AI研究的未来方向。跨机构广泛数据集的可获取性不断提高以及多参数MRI的应用,正显著提升AI的准确性和适应性。这一进展有可能实现更准确、高效的诊断,为妇产科领域的个性化医疗带来机遇。

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