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Interactive Histology of Large-Scale Biomedical Image Stacks

Won-Ki Jeong, Jens Schneider, Stephen G. Turney, Beverly E. Faulkner-Jones, Dominik Meyer, Rudiger Westermann, R. Clay Reid, Jeff Lichtman, Hanspeter Pfister
Harvard University
IEEE Transactions on Visualization and Computer Graphics, November/December 2010 (vol. 16 no. 6) pp. 1386-1395

@article{jeong2010interactive,

   title={Interactive Histology of Large-Scale Biomedical Image Stacks},

   author={Jeong, W.K. and Schneider, J. and Turney, SG and Faulkner-Jones, B.E. and Meyer, D. and Westermann, R. and Reid, R.C. and Lichtman, J. and Pfister, H.},

   journal={Visualization and Computer Graphics, IEEE Transactions on},

   volume={16},

   number={6},

   pages={1386–1395},

   year={2010},

   publisher={IEEE}

}

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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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