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      QuPath: Open source software for digital pathology image analysis

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          Abstract

          QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath’s flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.

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          Most cited references22

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          NIH Image to ImageJ: 25 years of image analysis.

          Lynda C. Schneider, Wayne S Rasband (2013)
          For the past 25 years NIH Image and ImageJ software have been pioneers as open tools for the analysis of scientific images. We discuss the origins, challenges and solutions of these two programs, and how their history can serve to advise and inform other software projects.
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            Metadata matters: access to image data in the real world

            Melissa Linkert, Curtis Rueden, Chris Allan … (2010)
            Data sharing is important in the biological sciences to prevent duplication of effort, to promote scientific integrity, and to facilitate and disseminate scientific discovery. Sharing requires centralized repositories, and submission to and utility of these resources require common data formats. This is particularly challenging for multidimensional microscopy image data, which are acquired from a variety of platforms with a myriad of proprietary file formats (PFFs). In this paper, we describe an open standard format that we have developed for microscopy image data. We call on the community to use open image data standards and to insist that all imaging platforms support these file formats. This will build the foundation for an open image data repository.
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              Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

              Douglas G. Altman, Lisa McShane, Willi Sauerbrei … (2012)
              The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies.
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                Author and article information

                Contributors
                Philip D. Dunne: (View ORCID Profile)
                Journal
                Title: Scientific Reports
                Abbreviated Title: Sci Rep
                Publisher: Springer Science and Business Media LLC
                ISSN (Electronic): 2045-2322
                Publication date Created: December 2017
                Publication date (Electronic): December 4 2017
                Publication date (Print): December 2017
                Volume: 7
                Issue: 1
                Article
                DOI: 10.1038/s41598-017-17204-5
                SO-VID: 6fe84731-6303-4a2a-a0f5-abc5ca445479
                Copyright © © 2017
                License:

                http://creativecommons.org/licenses/by/4.0

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