数字化病理学
工作流程
数字化
元数据
计算机科学
数据科学
资源(消歧)
分析
过程(计算)
数据整理
大数据
病理
万维网
医学
人工智能
数据库
数据挖掘
操作系统
计算机网络
计算机视觉
作者
Xing-Yue M. Ge,Juergen Funk,Tom Albrecht,Merima Birkhimer,Moritz Gilsdorf,Matthew Hayes,Fangyao Hu,Pierre Maliver,Mark McCreary,Nguyễn Trung Kiên,F. Romero-Palomo,Shanon Seger,Reina N. Fuji,Vanessa Schumacher,Ruth Sullivan
标识
DOI:10.1177/01926233221132747
摘要
Digitization of histologic slides brings with it the promise of enhanced toxicologic pathology practice through the increased application of computational methods. However, the development of these advanced methods requires access to substrate image data, that is, whole slide images (WSIs). Deep learning methods, in particular, rely on extensive training data to develop robust algorithms. As a result, pharmaceutical companies interested in leveraging computational methods in their digital pathology workflows must first invest in data infrastructure to enable data access for both data scientists and pathologists. The process of building robust image data resources is challenging and includes considerations of generation, curation, and storage of WSI files, and WSI access including via linked metadata. This opinion piece describes the collective experience of building resources for WSI data in the Roche group. We elaborate on the challenges encountered and solutions developed with the goal of providing examples of how to build a data resource for digital pathology analytics in the pharmaceutical industry.
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