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.
|Number of pages
|IEEE Transactions on Visualization and Computer Graphics
|Published - 2010
Bibliographical noteFunding Information:
This work was supported in part by the National Science Foundation under Grant No. PHY-0835713, the National Institutes of Health under Grant No. 1P30NS062685-01 and R01 NS020364-23, The Gatsby Charitable Foundation under Grant GAT3036-Connectomic Consortium, and through generous support from Microsoft Research and NVIDIA. We wish to thank Dr. Su-Jean Seo for participating in the user study.
- Gigapixel viewer
- biomedical image processing
- texture compression
ASJC Scopus subject areas
- Signal Processing
- Computer Vision and Pattern Recognition
- Computer Graphics and Computer-Aided Design