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QuPath:一个开源数字病理系统的全球影响力

QuPath: The global impact of an open source digital pathology system.

作者信息

Humphries M P, Maxwell P, Salto-Tellez M

机构信息

Precision Medicine Centre of Excellence, The Patrick G Johnston Centre for Cancer Research, Queen's University, Belfast, UK.

Integrated Pathology Programme, Division of Molecular Pathology, The Institute of Cancer Research, London, UK.

出版信息

Comput Struct Biotechnol J. 2021 Jan 21;19:852-859. doi: 10.1016/j.csbj.2021.01.022. eCollection 2021.

Abstract

QuPath, originally created at the Centre for Cancer Research & Cell Biology at Queen's University Belfast as part of a research programme in digital pathology (DP) funded by Invest Northern Ireland and Cancer Research UK, is arguably the most wildly used image analysis software program in the world. On the back of the explosion of DP and a need to comprehensively visualise and analyse whole slides images (WSI), QuPath was developed to address the many needs associated with tissue based image analysis; these were several fold and, predominantly, translational in nature: from the requirement to visualise images containing billions of pixels from files several GBs in size, to the demand for high-throughput reproducible analysis, which the paradigm of routine visual pathological assessment continues to struggle to deliver. Resultantly, large-scale biomarker quantification must increasingly be augmented with DP. Here we highlight the impact of the open source Quantitative Pathology & Bioimage Analysis DP system since its inception, by discussing the scope of scientific research in which QuPath has been cited, as the system of choice for researchers.

摘要

QuPath最初是由贝尔法斯特女王大学癌症研究与细胞生物学中心创建的,作为北爱尔兰投资局和英国癌症研究中心资助的数字病理学(DP)研究项目的一部分。可以说,它是世界上使用最广泛的图像分析软件程序。在数字病理学蓬勃发展以及需要全面可视化和分析全切片图像(WSI)的背景下,QuPath应运而生,以满足与基于组织的图像分析相关的诸多需求;这些需求是多方面的,并且主要具有转化性质:从可视化包含数十亿像素、大小达数GB文件的图像的要求,到对高通量可重复分析的需求,而常规视觉病理评估模式仍难以满足这一需求。因此,大规模生物标志物定量分析必须越来越多地借助数字病理学。在此,我们通过讨论将QuPath作为首选系统引用的科研范围,突出了开源定量病理学与生物图像分析数字病理学系统自创建以来的影响。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/56a7/7851421/71e168236a6a/gr1.jpg

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