Title :
Interactive Histology of Large-Scale Biomedical Image Stacks
Author :
Won-Ki Jeong ; Schneider, J. ; Turney, S.G. ; Faulkner-Jones, B.E. ; Meyer, D. ; Westermann, R. ; Reid, R.C. ; Lichtman, J. ; Pfister, H.
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.
Keywords :
biological tissues; data compression; image coding; image resolution; image texture; medical image processing; microscopy; GPU-accelerated texture compression; biological tissue; digital imaging technology; digital pathology; display-aware processing; interactive histology; large-scale biomedical image stacks; microscopy techniques; nanoscale-resolution; serial electron micrographs; Data structures; Graphics processing unit; Image coding; Image resolution; Microscopy; Pathology; GPU; Gigapixel viewer; biomedical image processing; texture compression; Computer Graphics; Histological Techniques; Humans; Image Processing, Computer-Assisted; Microscopy, Electron, Transmission;
Journal_Title :
Visualization and Computer Graphics, IEEE Transactions on
DOI :
10.1109/TVCG.2010.168