xOpat: eXplainable Open Pathology Analysis Tool

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dc.contributor.authorHorák, Jiríen_US
dc.contributor.authorFurmanová, Katarínaen_US
dc.contributor.authorKozlíková, Barboraen_US
dc.contributor.authorBrázdil, Tomášen_US
dc.contributor.authorHolub, Petren_US
dc.contributor.authorKacenga, Martinen_US
dc.contributor.authorGallo, Matejen_US
dc.contributor.authorNenutil, Rudolfen_US
dc.contributor.authorByška, Janen_US
dc.contributor.authorRusnak, Viten_US
dc.contributor.editorBujack, Roxanaen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorSchreck, Tobiasen_US
dc.date.accessioned2023-06-10T06:16:22Z
dc.date.available2023-06-10T06:16:22Z
dc.date.issued2023
dc.description.abstractHistopathology research quickly evolves thanks to advances in whole slide imaging (WSI) and artificial intelligence (AI). However, existing WSI viewers are tailored either for clinical or research environments, but none suits both. This hinders the adoption of new methods and communication between the researchers and clinicians. The paper presents xOpat, an open-source, browserbased WSI viewer that addresses these problems. xOpat supports various data sources, such as tissue images, pathologists' annotations, or additional data produced by AI models. Furthermore, it provides efficient rendering of multiple data layers, their visual representations, and tools for annotating and presenting findings. Thanks to its modular, protocol-agnostic, and extensible architecture, xOpat can be easily integrated into different environments and thus helps to bridge the gap between research and clinical practice. To demonstrate the utility of xOpat, we present three case studies, one conducted with a developer of AI algorithms for image segmentation and two with a research pathologist.en_US
dc.description.number3
dc.description.sectionheadersScalar and Vector Fields
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume42
dc.identifier.doi10.1111/cgf.14812
dc.identifier.issn1467-8659
dc.identifier.pages63-73
dc.identifier.pages11 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.14812
dc.identifier.urihttps://diglib.eg.org:443/handle/10.1111/cgf14812
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subjectCCS Concepts: Human-centered computing -> Visualization systems and tools; Scientific visualization
dc.subjectHuman centered computing
dc.subjectVisualization systems and tools
dc.subjectScientific visualization
dc.titlexOpat: eXplainable Open Pathology Analysis Toolen_US
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