psudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloring

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dc.contributor.authorWarchol, Simonen_US
dc.contributor.authorTroidl, Jakoben_US
dc.contributor.authorMuhlich, Jeremyen_US
dc.contributor.authorKrueger, Roberten_US
dc.contributor.authorHoffer, Johnen_US
dc.contributor.authorLin, Ticaen_US
dc.contributor.authorBeyer, Johannaen_US
dc.contributor.authorGlassman, Elenaen_US
dc.contributor.authorSorger, Peteren_US
dc.contributor.authorPfister, Hanspeteren_US
dc.contributor.editorAigner, Wolfgangen_US
dc.contributor.editorArchambault, Danielen_US
dc.contributor.editorBujack, Roxanaen_US
dc.date.accessioned2024-05-21T08:19:20Z
dc.date.available2024-05-21T08:19:20Z
dc.date.issued2024
dc.description.abstractOver the past century, multichannel fluorescence imaging has been pivotal in myriad scientific breakthroughs by enabling the spatial visualization of proteins within a biological sample. With the shift to digital methods and visualization software, experts can now flexibly pseudocolor and combine image channels, each corresponding to a different protein, to explore their spatial relationships. We thus propose psudo, an interactive system that allows users to create optimal color palettes for multichannel spatial data. In psudo, a novel optimization method generates palettes that maximize the perceptual differences between channels while mitigating confusing color blending in overlapping channels. We integrate this method into a system that allows users to explore multi-channel image data and compare and evaluate color palettes for their data. An interactive lensing approach provides on-demand feedback on channel overlap and a color confusion metric while giving context to the underlying channel values. Color palettes can be applied globally or, using the lens, to local regions of interest. We evaluate our palette optimization approach using three graphical perception tasks in a crowdsourced user study with 150 participants, showing that users are more accurate at discerning and comparing the underlying data using our approach. Additionally, we showcase psudo in a case study exploring the complex immune responses in cancer tissue data with a biologist.en_US
dc.description.number3
dc.description.sectionheadersPerception and Cognition
dc.description.seriesinformationComputer Graphics Forum
dc.description.volume43
dc.identifier.doi10.1111/cgf.15103
dc.identifier.issn1467-8659
dc.identifier.pages14 pages
dc.identifier.urihttps://doi.org/10.1111/cgf.15103
dc.identifier.urihttps://diglib.eg.org/handle/10.1111/cgf15103
dc.publisherThe Eurographics Association and John Wiley & Sons Ltd.en_US
dc.subjectCCS Concepts: Human-centered computing → Visualization systems and tools
dc.subjectHuman centered computing → Visualization systems and tools
dc.titlepsudo: Exploring Multi-Channel Biomedical Image Data with Spatially and Perceptually Optimized Pseudocoloringen_US
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