人工智能在子宫内膜异位症成像中的应用。

IF 2.2 3区 医学 Q2 RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING
Sneha Mittal, Angela Tong, Scott Young, Priyanka Jha
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引用次数: 0

摘要

人工智能(AI)可能有潜力改善子宫内膜异位症成像中现有的诊断挑战。为了更好地指导未来的研究,本文概述了人工智能在子宫内膜异位症成像中的应用概况。来自PubMed的文章代表了人工智能在子宫内膜异位症成像中的不同应用方法。目前的子宫内膜异位症成像文献主要集中在人工智能在超声(US)和磁共振成像(MRI)中的应用。大多数研究使用美国数据,目前MRI研究有限。美国大多数研究采用经阴道超声(TVUS)数据,旨在检测深部子宫内膜异位症植入物、子宫腺肌症、子宫内膜异位症和子宫内膜异位症的继发症状。大多数MRI研究评估子宫内膜异位症的诊断和分割。一些研究分析了子宫内膜异位症的多模态成像方法,将US和MRI资料相结合或将影像学资料与临床资料相结合。目前的文献缺乏通用性和规范性。本综述中的大多数研究采用回顾性方法和单中心数据的小样本量。现有模型只关注狭窄的疾病检测或诊断问题,缺乏标准化的基础事实。总的来说,人工智能在子宫内膜异位症成像分析中的应用尚处于早期阶段,持续的研究对于开发和增强这些模型至关重要。
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 applications in endometriosis imaging

Artificial intelligence (AI) may have the potential to improve existing diagnostic challenges in endometriosis imaging. To better direct future research, this descriptive review summarizes the general landscape of AI applications in endometriosis imaging. Articles from PubMed were selected to represent different approaches to AI applications in endometriosis imaging. Current endometriosis imaging literature focuses on AI applications in ultrasound (US) and magnetic resonance imaging (MRI). Most studies use US data, with MRI studies being limited at present. The majority of US studies employ transvaginal ultrasound (TVUS) data and aim to detect deep endometriosis implants, adenomyosis, endometriomas, and secondary signs of endometriosis. Most MRI studies evaluate endometriosis disease diagnosis and segmentation. Some studies analyze multi-modal methods for endometriosis imaging, combining US and MRI data or using imaging data in combination with clinical data. Current literature lacks generalizability and standardization. Most studies in this review utilize small sample sizes with retrospective approaches and single-center data. Existing models only focus on narrow disease detection or diagnosis questions and lack standardized ground truth. Overall, AI applications in endometriosis imaging analysis are in their early stages, and continued research is essential to develop and enhance these models.

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来源期刊
Abdominal Radiology
Abdominal Radiology Medicine-Radiology, Nuclear Medicine and Imaging
CiteScore
5.20
自引率
8.30%
发文量
334
期刊介绍: Abdominal Radiology seeks to meet the professional needs of the abdominal radiologist by publishing clinically pertinent original, review and practice related articles on the gastrointestinal and genitourinary tracts and abdominal interventional and radiologic procedures. Case reports are generally not accepted unless they are the first report of a new disease or condition, or part of a special solicited section. Reasons to Publish Your Article in Abdominal Radiology: · Official journal of the Society of Abdominal Radiology (SAR) · Published in Cooperation with: European Society of Gastrointestinal and Abdominal Radiology (ESGAR) European Society of Urogenital Radiology (ESUR) Asian Society of Abdominal Radiology (ASAR) · Efficient handling and Expeditious review · Author feedback is provided in a mentoring style · Global readership · Readers can earn CME credits
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