人工智能在卵巢癌医学影像中的应用进展

陈旭; 吴哲; 陆菁菁

doi:10.24920/003963

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人工智能在卵巢癌医学影像中的应用进展

中国医学科学杂志（英文版） 2021年36卷第3期页码：196-203

综述 | Updated：2024-04-10

- 人工智能在卵巢癌医学影像中的应用进展
- Affiliations：
  
  1. 1Department of Radiology, Beijing United Family Hospital, Beijing 100015, China
  2. 2Department of Radiology, Fushun Central Hospital, Fushun, Liaoning 113006, China
- Author bio：
  
  *Tel: 86-13501398521; E-mail: cjr.lujingjing@vip.163.com
- Funds：
- DOI：10.24920/003963
  中图分类号：
- 收稿日期：2021-06-30，
  
  录用日期：2021-8-24，
  
  纸质出版日期：2021-08-30
- Accepted：
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陈旭, 吴哲, 陆菁菁. 人工智能在卵巢癌医学影像中的应用进展[J]. 中国医学科学杂志（英文版）, 2021,36(3):196-203.

Xu Chen, Xiaofei Huo, Zhe Wu, et al. Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers[J]. Chinese medical sciences journal, 2021, 36(3): 196-203.
陈旭, 吴哲, 陆菁菁. 人工智能在卵巢癌医学影像中的应用进展[J]. 中国医学科学杂志（英文版）, 2021,36(3):196-203. DOI： 10.24920/003963.

Xu Chen, Xiaofei Huo, Zhe Wu, et al. Advances of Artificial Intelligence Application in Medical Imaging of Ovarian Cancers[J]. Chinese medical sciences journal, 2021, 36(3): 196-203. DOI： 10.24920/003963.

摘要

卵巢癌是世界范围内常见的三大妇科恶性肿瘤之一

但病死率居首位。近年来

许多医学及工程技术研究尝试将人工智能（artificial intelligence

AI）技术应用于卵巢癌诊治的多个临床场景中

在医学影像AI技术的开发与应用中取得了较为丰富的进展。AI相关的医学影像研究主要涉及计算机断层扫描、超声成像和磁共振成像。我们对AI在卵巢癌医学影像方面的已发表的研究进行了文献检索和回顾

从卵巢癌的影像诊断、病理分类

靶向活检引导以及预后预测四个方面深入分析了医学影像领域AI相关研究的最新进展

同时对其现状及存在的问题进行了相应阐述。

Abstract

Ovarian cancer is one of the three most common gynecological cancers in the world

and is regarded as a priority in terms of women’s cancer. In the past few years

many researchers have attempted to develop and apply artificial intelligence (AI) techniques to multiple clinical scenarios of ovarian cancer

especially in the field of medical imaging. AI-assisted imaging studies have involved computer tomography (CT)

ultrasonography (US)

and magnetic resonance imaging (MRI). In this review

we perform a literature search on the published studies that using AI techniques in the medical care of ovarian cancer

and bring up the advances in terms of four clinical aspects

including medical diagnosis

pathological classification

targeted biopsy guidance

and prognosis prediction. Meanwhile

current status and existing issues of the researches on AI application in ovarian cancer are discussed.

关键词

Keywords

references

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