Interactive histology of large-scale biomedical image stacks

W. Jeong, J. Schneider, S.G. Turney, B. E. Faulkner-Jones, D. Meyer, R. Westermann, C.R. Reid, J. Lichtman, H. Pfister
IEEE Transactions on Visualization and Computer Graphics, 16(6), 1386-1395, (2010)

Interactive histology of large-scale biomedical image stacks

Keywords

Biomedical image stack

Abstract

​Our display-aware gigapixel image viewer for biomedical image stacks. Input image stacks are processed and stored individually (green rectangles to the left, 360 image stacks each comprising 2.7K × 2K × 16 samples, resulting in over 30 gigapixels), but the globally consistent view for an arbitrary zoom level and image plane can be composed on-the-fly (right). The proposed system provides an interactive digital pathology workflow that allows fast changes in pan, zoom, and focus. 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 GPUaccelerated texture compression. With display-aware processing, only the currently visible image tiles are fetched and aligned on-thefly, 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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