The Digital Slide Archive: A Software Platform for Management, Integration, and Analysis of Histology for Cancer Research.

Autor:	Gutman DA; Department of Neurology, Emory University School of Medicine, Atlanta, Georgia. dgutman@emory.edu.; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia.; Winship Cancer Institute, Emory University, Atlanta, Georgia., Khalilia M; Department of Neurology, Emory University School of Medicine, Atlanta, Georgia., Lee S; Department of Neurology, Emory University School of Medicine, Atlanta, Georgia., Nalisnik M; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia., Mullen Z; Kitware Incorporated, Clifton Park, New York., Beezley J; Kitware Incorporated, Clifton Park, New York., Chittajallu DR; Kitware Incorporated, Clifton Park, New York., Manthey D; Kitware Incorporated, Clifton Park, New York., Cooper LAD; Department of Biomedical Informatics, Emory University School of Medicine, Atlanta, Georgia.; Winship Cancer Institute, Emory University, Atlanta, Georgia.; Department of Biomedical Engineering, Emory University School of Medicine/Georgia Institute of Technology, Atlanta, Georgia.
Jazyk:	angličtina
Zdroj:	Cancer research [Cancer Res] 2017 Nov 01; Vol. 77 (21), pp. e75-e78.
DOI:	10.1158/0008-5472.CAN-17-0629
Abstrakt:	Tissue-based cancer studies can generate large amounts of histology data in the form of glass slides. These slides contain important diagnostic, prognostic, and biological information and can be digitized into expansive and high-resolution whole-slide images using slide-scanning devices. Effectively utilizing digital pathology data in cancer research requires the ability to manage, visualize, share, and perform quantitative analysis on these large amounts of image data, tasks that are often complex and difficult for investigators with the current state of commercial digital pathology software. In this article, we describe the Digital Slide Archive (DSA), an open-source web-based platform for digital pathology. DSA allows investigators to manage large collections of histologic images and integrate them with clinical and genomic metadata. The open-source model enables DSA to be extended to provide additional capabilities. Cancer Res; 77(21); e75-78. ©2017 AACR . (©2017 American Association for Cancer Research.)
Databáze:	MEDLINE
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