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

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Interactive Histology of Large-Scale Biomedical Image Stacks

Cited 8 times inthomson ciCited 8 times inthomson ci
Title
Interactive Histology of Large-Scale Biomedical Image Stacks
Author
Jeong, Won-KiSchneider, JensTurney, Stephen G.Faulkner-Jones, Beverly E.Meyer, DominikWestermann, RuedigerReid, R. ClayLichtman, JeffPfister, Hanspeter
Keywords
biomedical image processing; Gigapixel viewer; GPU; texture compression
Issue Date
2010-11
Publisher
IEEE COMPUTER SOC
Citation
IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS, v.16, no.6, pp.1386 - 1395
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.
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DOI
10.1109/TVCG.2010.168
ISSN
1077-2626
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EE_Journal Papers
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