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数字脑肿瘤图谱,一个开放的组织病理学资源。

The Digital Brain Tumour Atlas, an open histopathology resource.

机构信息

Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria.

Department of Neurosurgery, Medical University of Vienna, Vienna, Austria.

出版信息

Sci Data. 2022 Feb 15;9(1):55. doi: 10.1038/s41597-022-01157-0.

Abstract

Currently, approximately 150 different brain tumour types are defined by the WHO. Recent endeavours to exploit machine learning and deep learning methods for supporting more precise diagnostics based on the histological tumour appearance have been hampered by the relative paucity of accessible digital histopathological datasets. While freely available datasets are relatively common in many medical specialties such as radiology and genomic medicine, there is still an unmet need regarding histopathological data. Thus, we digitized a significant portion of a large dedicated brain tumour bank based at the Division of Neuropathology and Neurochemistry of the Medical University of Vienna, covering brain tumour cases from 1995-2019. A total of 3,115 slides of 126 brain tumour types (including 47 control tissue slides) have been scanned. Additionally, complementary clinical annotations have been collected for each case. In the present manuscript, we thoroughly discuss this unique dataset and make it publicly available for potential use cases in machine learning and digital image analysis, teaching and as a reference for external validation.

摘要

目前,世界卫生组织(WHO)定义了大约 150 种不同的脑肿瘤类型。最近,人们试图利用机器学习和深度学习方法,根据组织病理学肿瘤外观进行更精确的诊断,但由于可获取的数字化组织病理学数据集相对较少,这些努力受到了阻碍。虽然在放射学和基因组医学等许多医学专业中,免费提供的数据集相对常见,但在组织病理学数据方面仍存在未满足的需求。因此,我们对维也纳医科大学神经病理学和神经化学系的一个大型脑肿瘤库进行了大量数字化处理,涵盖了 1995 年至 2019 年的脑肿瘤病例。共扫描了 3115 张 126 种脑肿瘤类型的幻灯片(包括 47 张对照组织幻灯片),并为每个病例收集了补充的临床注释。在本研究中,我们详细讨论了这个独特的数据集,并将其公开供机器学习和数字图像分析、教学以及作为外部验证参考的潜在用例使用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b69c/8847577/55da4e04547b/41597_2022_1157_Fig1_HTML.jpg

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