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用于解读数字病理学图像和组织图谱数据的叙事式在线指南。

Narrative online guides for the interpretation of digital-pathology images and tissue-atlas data.

机构信息

Laboratory of Systems Pharmacology, Harvard Medical School, Boston, MA, USA.

Ludwig Center at Harvard, Harvard Medical School, Boston, MA, USA.

出版信息

Nat Biomed Eng. 2022 May;6(5):515-526. doi: 10.1038/s41551-021-00789-8. Epub 2021 Nov 8.

Abstract

Multiplexed tissue imaging facilitates the diagnosis and understanding of complex disease traits. However, the analysis of such digital images heavily relies on the experience of anatomical pathologists for the review, annotation and description of tissue features. In addition, the wider use of data from tissue atlases in basic and translational research and in classrooms would benefit from software that facilitates the easy visualization and sharing of the images and the results of their analyses. In this Perspective, we describe the ecosystem of software available for the analysis of tissue images and discuss the need for interactive online guides that help histopathologists make complex images comprehensible to non-specialists. We illustrate this idea via a software interface (Minerva), accessible via web browsers, that integrates multi-omic and tissue-atlas features. We argue that such interactive narrative guides can effectively disseminate digital histology data and aid their interpretation.

摘要

多重组织成像有助于诊断和理解复杂的疾病特征。然而,这种数字图像的分析在很大程度上依赖于解剖病理学家的经验,用于审查、注释和描述组织特征。此外,组织图谱数据在基础和转化研究以及课堂中的更广泛应用将受益于能够方便地可视化和共享图像及其分析结果的软件。在本观点中,我们描述了可用于组织图像分析的软件生态系统,并讨论了需要交互式在线指南来帮助组织病理学家使复杂的图像易于非专业人士理解。我们通过一个软件界面(Minerva)来说明这个想法,该界面可以通过网络浏览器访问,集成了多组学和组织图谱的特征。我们认为,这种交互式叙述指南可以有效地传播数字组织学数据并帮助解释。

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