人工智能在妇产科磁共振成像中的应用。

Tsukasa Saida, Wenchao Gu, Sodai Hoshiai, Toshitaka Ishiguro, Masafumi Sakai, Taishi Amano, Yuta Nakahashi, Ayumi Shikama, Toyomi Satoh, Takahito Nakajima
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引用次数: 0

摘要

这篇综述探讨了人工智能(AI)在妇产科磁共振成像中的重大进展和应用,描绘了其从基础算法技术到深度学习策略和高级放射组学的发展历程。这篇综述介绍了过去几年发表的研究成果,这些研究将人工智能与核磁共振成像相结合,用于识别特定病症,如子宫肌层肉瘤、子宫内膜癌、宫颈癌、卵巢肿瘤和胎盘早剥。此外,它还涵盖了将人工智能应用于妇产科磁共振成像的分割和质量改进的研究。综述还概述了该领域人工智能研究的现有挑战和未来发展方向。不同机构间广泛数据集的日益普及以及多参数核磁共振成像的应用,大大提高了人工智能的准确性和适应性。这一进步有可能实现更准确、更高效的诊断,为妇产科领域的个性化医疗提供机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial Intelligence in Obstetric and Gynecological MR Imaging.

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.

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