title: Large-scale biomedical image analysis in grid environments.
abstract: 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.
authors: Department of Biomedical Informatics, Ohio State University, Columbus, OH 43210, USA. vijayskumar@bmi.osu.edu
authors: Vijay S
authors: VS
authors: Kumar
authors: Benjamin
authors: B
authors: Rutt
authors: Tahsin
authors: T
authors: Kurc
authors: Umit V
authors: UV
authors: Catalyurek
authors: Tony C
authors: TC
authors: Pan
authors: Sunny
authors: S
authors: Chow
authors: Stephan
authors: S
authors: Lamont
authors: Maryann
authors: M
authors: Martone
authors: Joel H
authors: JH
authors: Saltz
mesh_terms: 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