Interactive Histology of large-scale biomedical image stacks

  • Won Ki Jeong*
  • , Jens Schneider
  • , Stephen Turney
  • , Beverly E. Faulkner-Jones
  • , Dominik Meyer
  • , Rüdiger Westermann
  • , R. Clay Reid
  • , Jeff Lichtman
  • , Hanspeter Pfister
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number5613479
Pages (from-to)1386-1395
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Volume16
Issue number6
DOIs
Publication statusPublished - 2010
Externally publishedYes

Keywords

  • GPU
  • Gigapixel viewer
  • biomedical image processing
  • texture compression

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