The Community for Technology Leaders
Green Image
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.
Microscopy, Image coding, Image resolution, Pathology, Graphics processing unit, Data structures

Won-Ki Jeong et al., "Interactive Histology of Large-Scale Biomedical Image Stacks," in IEEE Transactions on Visualization & Computer Graphics, vol. 16, no. 6, pp. 1386-1395, 2010.
359 ms
(Ver 3.3 (11022016))