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Advances in Digital Pathology: From Artificial Intelligence to Label-Free Imaging
Visceral Medicine ( IF 1.9 ) Pub Date : 2021-08-24 , DOI: 10.1159/000518494
Frederik Großerueschkamp 1, 2 , Hendrik Jütte 1, 3 , Klaus Gerwert 1, 2 , Andrea Tannapfel 1, 3
Affiliation  

Background: Digital pathology, in its primary meaning, describes the utilization of computer screens to view scanned histology slides. Digitized tissue sections can be easily shared for a second opinion. In addition, it allows tissue image analysis using specialized software to identify and measure events previously observed by a human observer. These tissue-based readouts were highly reproducible and precise. Digital pathology has developed over the years through new technologies. Currently, the most discussed development is the application of artificial intelligence to automatically analyze tissue images. However, even new label-free imaging technologies are being developed to allow imaging of tissues by means of their molecular composition. Summary: This review provides a summary of the current state-of-the-art and future digital pathologies. Developments in the last few years have been presented and discussed. In particular, the review provides an outlook on interesting new technologies (e.g., infrared imaging), which would allow for deeper understanding and analysis of tissue thin sections beyond conventional histopathology. Key Messages: In digital pathology, mathematical methods are used to analyze images and draw conclusions about diseases and their progression. New innovative methods and techniques (e.g., label-free infrared imaging) will bring significant changes in the field in the coming years.
Visc Med


中文翻译:

数字病理学的进展:从人工智能到无标记成像

背景:数字病理学,在其主要含义中,描述了利用计算机屏幕查看扫描的组织学幻灯片。数字化的组织切片可以轻松共享以征求第二意见。此外,它还允许使用专门的软件进行组织图像分析,以识别和测量人类观察者之前观察到的事件。这些基于组织的读数具有高度可重复性和精确性。多年来,数字病理学通过新技术得到了发展。目前,讨论最多的发展是应用人工智能自动分析组织图像。然而,甚至正在开发新的无标记成像技术,以允许通过分子组成对组织进行成像。概括:这篇综述总结了当前最先进的和未来的数字病理学。介绍和讨论了过去几年的发展。特别是,该综述提供了对有趣的新技术(例如红外成像)的展望,这将允许在传统组织病理学之外更深入地理解和分析组织薄切片。关键信息:在数字病理学中,数学方法用于分析图像并得出有关疾病及其进展的结论。新的创新方法和技术(例如,无标记红外成像)将在未来几年为该领域带来重大变化。
维斯克医学
更新日期:2021-08-24
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