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dc.contributor.authorWan, Yongen_US
dc.contributor.authorOtsuna, Hideoen_US
dc.contributor.authorKwan, K. M.en_US
dc.contributor.authorHansen, Charlesen_US
dc.contributor.editorIvan Viola and Katja Buehler and Timo Ropinskien_US
dc.date.accessioned2014-12-16T07:36:55Z
dc.date.available2014-12-16T07:36:55Z
dc.date.issued2014en_US
dc.identifier.isbn978-3-905674-62-0en_US
dc.identifier.issn2070-5778en_US
dc.identifier.urihttp://dx.doi.org/10.2312/vcbm.20141184en_US
dc.identifier.urihttp://hdl.handle.net/10.2312/vcbm.20141184.059-068
dc.description.abstractSelecting structures from volume data using direct over-the-visualization interactions, such as a paint brush, is perhaps the most intuitive method in a variety of application scenarios. Unfortunately, it seems difficult to design a universal tool that is effective for all different structures in biology research. In [WOCH12b], an interactive technique was proposed for extracting neural structures from confocal microscopy data. It uses a dual-stroke paint brush to select desired structures directly from volume visualizations. However, the technique breaks down when it was applied to selecting densely packed structures with condensed shapes, such as nuclei from zebrafish eye development research. We collaborated with biologists studying zebrafish eye development and adapted the paint brush tool for real-time nucleus selection from volume data. The morphological diffusion algorithm used in the previous paint brush is restricted to gradient descending directions for improved nucleus boundary definition. Occluded seeds are removed using backward ray-casting. The adapted paint brush is then used in tracking cell movements in a time sequence dataset of a developing zebrafish eye.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectI.3.8 [Computer Graphics]en_US
dc.subjectMethodology and Techniquesen_US
dc.subjectInteraction techniquesen_US
dc.subjecten_US
dc.subjectJ.3 [Life and Medical Sciences]en_US
dc.subjectBiology and geneticsen_US
dc.titleReal-Time Dense Nucleus Selection from Confocal Dataen_US
dc.description.seriesinformationEurographics Workshop on Visual Computing for Biology and Medicineen_US


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