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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.
INDEX TERMS
Microscopy, Image coding, Image resolution, Pathology, Graphics processing unit, Data structures,texture compression, Gigapixel viewer, biomedical image processing, GPU
CITATION
Won-Ki Jeong, J Schneider, Stephen G Turney, B E Faulkner-Jones, D Meyer, Rüdiger Westermann, R C Reid, J Lichtman, H Pfister, "Interactive Histology of Large-Scale Biomedical Image Stacks", IEEE Transactions on Visualization & Computer Graphics, vol. 16, no. , pp. 1386-1395, November/December 2010, doi:10.1109/TVCG.2010.168
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