Dr. Bankhead completed his PhD at Queen’s University Belfast, focusing on the analysis of retinal images and calcium signals in retinal arterioles. He then moved to Germany, becoming a postdoc in the Nikon Imaging Center at Heidelberg University where he spent much of his time helping microscope users analyze their imaging data using open source software. During this time he wrote a popular bioimage analysis handbook for biologists (https://petebankhead.gitbooks.io/imagej-intro/content/).
Upon returning to Belfast at the end of 2012, Dr Bankhead encountered digital pathology for the first time as a postdoc in Prof. Peter Hamilton’s group at Queen’s. After trying to apply existing open software tools to whole slide images with limited success, he wrote his own: QuPath (https://qupath.github.io).
Title: QuPath: Open source software to revolutionize & standardize digital pathology analysis
Abstract:
Innovation increasingly relies on open tools, standards and software, empowering researchers to test new ideas and make new discoveries. Reproducibility and standardization in science also crucially depend upon analysis methods being made freely available.
Until recently, digital pathology suffered from the lack of a software platform that would make these things possible. Faced with a choice between attempting to analyze whole slide images using commercial systems (often prohibitively expensive) or by applying generic open source software (often prohibitively complex), much biomarker analysis in practice continued to be based on visual estimation by pathologists, which is laborious and known to have limited reproducibility.
QuPath was developed to address these issues, and represents the first widely-used, powerful, flexible, extensible and user-friendly open source platform for whole slide image analysis. Since its release at the end of 2016, QuPath has been downloaded more than 10 000 times and is used worldwide by research groups in both academia and industry.
A central goal of QuPath is to provide the tools for pathologists and image analysts to better work together, advancing the field more rapidly. This presentation outlines a few of the reasons behind QuPath’s success so far, and describes features currently in development that are set to greatly expand its scope and reach for digital pathology and bioimage analysis applications in the near future.