Suppr超能文献

加强多学科合作,推进医学图像感知研究。

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration.

机构信息

Behavioral Research Program, National Cancer Institute, Rockville, MD, USA.

Clinical Research in Complementary and Integrative Health Branch, National Center for Complementary and Integrative Health, Rockville, MD, USA.

出版信息

JNCI Cancer Spectr. 2022 Jan 5;6(1). doi: 10.1093/jncics/pkab099.

Abstract

Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians' accuracy and performance, improving patient outcomes, and reducing diagnostician burnout. Medical image perception remains substantially understudied. In September 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the "Cognition and Medical Image Perception Think Tank." The Think Tank's key objectives were to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians, discuss how these clinically relevant questions could be addressed through cognitive and perception research, identify barriers and solutions for transdisciplinary collaborations, define ways to elevate the profile of cognition and perception research within the medical image community, determine the greatest needs to advance medical image perception, and outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians' perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This article reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.

摘要

医学图像解释是检测、诊断和分期癌症和许多其他疾病的核心。在数字技术和人工智能正在改变医学成像的时代,了解医学图像解释的基本感知和认知过程对于提高诊断医生的准确性和性能、改善患者预后和减少诊断医生的倦怠至关重要。医学图像感知仍然在很大程度上未被充分研究。2019 年 9 月,美国国家癌症研究所召集了一个由放射科医生和病理学家组成的多学科小组,以及从事医学图像感知以及认知和感知相关领域研究的研究人员,参加了“认知与医学图像感知智库”。智库的主要目标是从诊断医生的角度确定与病理学和放射学中的视觉感知相关的关键未解决问题,讨论如何通过认知和感知研究来解决这些与临床相关的问题,确定跨学科合作的障碍和解决方案,确定在医学图像界提升认知和感知研究形象的方法,确定推进医学图像感知的最大需求,并概述未来的目标和策略以评估进展。智库强调诊断医生的观点是医学图像感知研究的关键起点,诊断医生描述他们的解释过程并确定出现的感知和认知问题。本文报告了智库参与者为解决这些目标和突出扩大医学图像感知研究的机会而进行的审议。

相似文献

2
Volumetric image interpretation in radiology: scroll behavior and cognitive processes.放射学中的容积图像解读:滚动行为与认知过程。
Adv Health Sci Educ Theory Pract. 2018 Oct;23(4):783-802. doi: 10.1007/s10459-018-9828-z. Epub 2018 May 16.
5
The future of Cochrane Neonatal.考克兰新生儿协作网的未来。
Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12.

引用本文的文献

1
Controllable Medical Image Generation via GAN.通过生成对抗网络实现可控医学图像生成
J Percept Imaging. 2022 Jan;5:0005021-50215. doi: 10.2352/j.percept.imaging.2022.5.000502. Epub 2022 Mar 18.
3
Relative tuning of holistic face processing towards the fovea.整体面部加工向中央凹的相对调谐。
Vision Res. 2022 Aug;197:108049. doi: 10.1016/j.visres.2022.108049. Epub 2022 Apr 20.

本文引用的文献

4
PRISM: A Platform for Imaging in Precision Medicine.PRISM:精准医学成像平台。
JCO Clin Cancer Inform. 2020 Jun;4:491-499. doi: 10.1200/CCI.20.00001.
5
International evaluation of an AI system for breast cancer screening.国际乳腺癌筛查人工智能系统评估。
Nature. 2020 Jan;577(7788):89-94. doi: 10.1038/s41586-019-1799-6. Epub 2020 Jan 1.
6
Integrated diagnostics: the future of laboratory medicine?整合诊断:检验科的未来?
Biochem Med (Zagreb). 2020 Feb 15;30(1):010501. doi: 10.11613/BM.2020.010501. Epub 2019 Dec 15.
8
The pop-up research centre - Challenges and opportunities.弹出式研究中心——挑战与机遇。
Radiography (Lond). 2019 Oct;25 Suppl 1:S19-S24. doi: 10.1016/j.radi.2019.05.009. Epub 2019 Jun 26.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验