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dc.contributor.authorBankhead, Peter
dc.date.accessioned2018-11-29T15:19:45Z
dc.date.available2018-11-29T15:19:45Z
dc.date.issued2018-11-23
dc.identifier.urihttp://hdl.handle.net/1842/33288
dc.description.abstractOpen source image analysis software plays a crucial role in biological research. For more than 20 years biologists have relied upon ImageJ to analyze microscopy data, and an ecosystem of open bioimage analysis tools (including Fiji, CellProfiler, ilastik, KNIME, icy) has since grown up to help researchers deal with the wide diversity of data across the field. However, until recently there was no established open source platform designed to handle whole slide images. These are ultra-large scans of entire glass slides (typically up to 50 GB per 2D image), the size and complexity of which pose unique computational challenges. Whole slide images are already the mainstay of digital pathology and are becoming increasingly common in other areas of biomedical research. I created QuPath to address this need (https://qupath.github.io), with the aim of making the analysis of complex tissue images containing millions of cells both fast and intuitive. Since its release less than 2 years ago, QuPath has becomeen
dc.language.isoenen
dc.publisherUniversity of Edinburghen
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectDwD2018en
dc.subjectOpen Sourceen
dc.subjectimage analysisen
dc.subjectQuPathen
dc.subjectopen sourceen
dc.subjectopen softwareen
dc.titleExperiences of open science & softwareen
dc.typePresentationen


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International