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Jeong, Won-Ki
High-performance Visual Computing Lab
Research Interests
  • Visualization, image processing, machine learning, parallel computing


Interactive Histology of Large-Scale Biomedical Image Stacks

DC Field Value Language Jeong, Won-Ki ko Schneider, Jens ko Turney, Stephen G. ko Faulkner-Jones, Beverly E. ko Meyer, Dominik ko Westermann, Ruediger ko Reid, R. Clay ko Lichtman, Jeff ko Pfister, Hanspeter ko 2014-10-30T00:09:34Z - 2014-10-29 ko 2010-11 -
dc.identifier.citation IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, v.16, no.6, pp.1386 - 1395 ko
dc.identifier.issn 1077-2626 ko
dc.identifier.uri -
dc.identifier.uri ko
dc.description.abstract Histology is the study of the structure of biological tissue using microscopy techniques. As digital imaging technology advances, high resolution microscopy of large tissue volumes is becoming feasible; however, new interactive tools are needed to explore and analyze the enormous datasets. In this paper we present a visualization framework that specifically targets interactive examination of arbitrarily large image stacks. Our framework is built upon two core techniques: display-aware processing and GPU-accelerated texture compression. With display-aware processing, only the currently visible image tiles are fetched and aligned on-the-fly, reducing memory bandwidth and minimizing the need for time-consuming global pre-processing. Our novel texture compression scheme for GPUs is tailored for quick browsing of image stacks. We evaluate the usability of our viewer for two histology applications: digital pathology and visualization of neural structure at nanoscale-resolution in serial electron micrographs. ko
dc.description.statementofresponsibility close -
dc.language ENG ko
dc.publisher IEEE COMPUTER SOC ko
dc.subject biomedical image processing ko
dc.subject Gigapixel viewer ko
dc.subject GPU ko
dc.subject texture compression ko
dc.title Interactive Histology of Large-Scale Biomedical Image Stacks ko
dc.type ARTICLE ko
dc.identifier.scopusid 2-s2.0-78149243509 ko
dc.identifier.wosid 000283758600059 ko
dc.type.rims ART ko
dc.description.wostc 8 *
dc.description.scopustc 8 * 2015-05-06 * 2014-10-29 *
dc.identifier.doi 10.1109/TVCG.2010.168 ko
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