The recent development of highly multiplexed tissue imaging promises to substantially accelerate research into basic biology and human disease. Concurrently, histopathology in a clinical setting is undergoing a rapid transition to digital methods. Online tissue atlases involving highly multiplexed images of research and clinical specimens will soon join genomics as a systematic source of information on the molecular basis of disease and therapeutic response. However, even with recent advances in machine learning, experience with anatomic pathology shows that there is no immediate substitute for expert visual review, annotation, and description of tissue images. In this perspective we review the ecosystem of software available for analysis of tissue images and identify a need for interactive guides, or digital docents, that allow experts to help make complex images intelligible. We illustrate this idea using Minerva software and discuss how interactive image guides are being integrated into multi-omic browsers for effective dissemination of atlas data.

中文翻译：

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在线叙事指南，用于照亮组织图谱数据和数字病理图像

高度复用的组织成像的最新发展有望大大加速对基础生物学和人类疾病的研究。同时，临床环境中的组织病理学正快速过渡到数字方法。涉及研究和临床标本的高度多重图像的在线组织图集将很快加入基因组学，成为疾病和治疗反应的分子基础上的系统信息源。但是，即使在机器学习方面有了最新进展，解剖病理学的经验也表明，并不能立即替代专家对组织图像的视觉检查，注释和描述。从这个角度来看，我们回顾了可用于组织图像分析的软件生态系统，并确定了对交互式指南或数字讲义的需求，使专家可以帮助您理解复杂的图像。我们使用Minerva软件说明了这一想法，并讨论了如何将交互式图像指南集成到多组浏览器中以有效传播地图集数据。