Large-scale biomedical image analysis in grid environments.
This paper presents the application of a component-based Grid middleware system for processing extremely large images obtained from digital microscopy devices. We have developed parallel, out-of-core techniques for different classes of data processing operations employed on images from confocal microscopy scanners. These techniques are combined into a data preprocessing and analysis pipeline using the component-based middleware system. The experimental results show that: 1) our implementation achieves good performance and can handle very large datasets on high-performance Grid nodes, consisting of computation and/or storage clusters and 2) it can take advantage of Grid nodes connected over high-bandwidth wide-area networks by combining task and data parallelism.
Kumar
Vijay S
VS
Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA. vijayskumar@bmi.osu.edu
Rutt
Benjamin
B
Kurc
Tahsin
T
Catalyurek
Umit V
UV
Pan
Tony C
TC
Chow
Sunny
S
Lamont
Stephan
S
Martone
Maryann
M
Saltz
Joel H
JH
D003628:Database Management Systems; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D033181:Information Dissemination / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods*; D020407:Internet; D008853:Microscopy / Q000379:methods*; D011873:Radiology Information Systems; D012815:Signal Processing, Computer-Assisted