Visual Analytics in Digital Pathology: Challenges and Opportunities

dc.contributor.authorCorvò, Albertoen_US
dc.contributor.authorWestenberg, Michel A.en_US
dc.contributor.authorWimberger-Friedl, Reinholden_US
dc.contributor.authorFromme, Stephanen_US
dc.contributor.authorPeeters, Michel M. R.en_US
dc.contributor.authorDriel, Marc A. vanen_US
dc.contributor.authorWijk, Jarke J. vanen_US
dc.contributor.editorKozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgiaen_US
dc.date.accessioned2019-09-03T13:49:10Z
dc.date.available2019-09-03T13:49:10Z
dc.date.issued2019
dc.description.abstractThe advances in high-throughput digitization, digital pathology systems, and quantitative image analysis opened new horizons in pathology. The diagnostic work of the pathologists and their role is likely to be augmented with computer-assistance and more quantitative information at hand. The recent success of artificial intelligence (AI) and computer vision methods demonstrated that in the coming years machines will support pathologists in typically tedious and highly subjective tasks and also in better patient stratification. In spite of clear future improvements in the diagnostic workflow, questions on how to effectively support the pathologists and how to integrate current data sources and quantitative information still persist. In this context, Visual Analytics (VA) - as the discipline that aids users to solve complex problems with an interactive and visual approach - can play a vital role to support the cognitive skills of pathologists and the large volumes of data available. To identify the main opportunities to employ VA in digital pathology systems, we conducted a survey with 20 pathologists to characterize the diagnostic practice and needs from a user perspective. From our findings, we discuss how VA can leverage quantitative image data to empower pathologists with new advanced digital pathology systems.en_US
dc.description.sectionheadersDigital Pathology, Surgery, and Anatomical Education
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicine
dc.identifier.doi10.2312/vcbm.20191240
dc.identifier.isbn978-3-03868-081-9
dc.identifier.issn2070-5786
dc.identifier.pages129-143
dc.identifier.urihttps://doi.org/10.2312/vcbm.20191240
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/vcbm20191240
dc.publisherThe Eurographics Associationen_US
dc.subjectComputer Graphics
dc.subjectApplications
dc.titleVisual Analytics in Digital Pathology: Challenges and Opportunitiesen_US
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