Interactive histology of large-scale biomedical image stacks.
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.
Jeong
Won-Ki
WK
Harvard University, USA. wkjeong@seas.harvard.edu
Schneider
Jens
J
Turney
Stephen G
SG
Faulkner-Jones
Beverly E
BE
Meyer
Dominik
D
Westermann
Rüdiger
R
Reid
R Clay
RC
Lichtman
Jeff
J
Pfister
Hanspeter
H
D003196:Computer Graphics; D006652:Histological Techniques / Q000706:statistics & numerical data*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000706:statistics & numerical data*; D046529:Microscopy, Electron, Transmission / Q000706:statistics & numerical data