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High-Performance Systems for in Silico Microscopy Imaging Studies

  • Fusheng Wang
  • Tahsin Kurc
  • Patrick Widener
  • Tony Pan
  • Jun Kong
  • Lee Cooper
  • David Gutman
  • Ashish Sharma
  • Sharath Cholleti
  • Vijay Kumar
  • Joel Saltz
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6254)

Abstract

High-resolution medical images from advanced instruments provide rich information about morphological and functional characteristics of biological systems. However, most of the information available in biomedical images remains underutilized in research projects. In this paper, we discuss the requirements and design of system support for composing, executing, and exploring in silico experiments involving microscopy images. This framework aims to provide building blocks for large scale, high-performance analytical image exploration systems, through rich metadata models, comprehensive query and data access capabilities, and efficient database and HPC support.

Keywords

Spatial Query Rule Engine Provenance Information Metadata Model Silico Experiment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Fusheng Wang
    • 1
  • Tahsin Kurc
    • 1
  • Patrick Widener
    • 1
  • Tony Pan
    • 1
  • Jun Kong
    • 1
  • Lee Cooper
    • 1
  • David Gutman
    • 1
  • Ashish Sharma
    • 1
  • Sharath Cholleti
    • 1
  • Vijay Kumar
    • 2
  • Joel Saltz
    • 1
  1. 1.Center for Comprehensive Informatics, and Department of Biomedical EngineeringEmory UniversityAtlantaUSA
  2. 2.Dept. of Computer Science and EngineeringOhio State UniversityColumbus, OhioUSA

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