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Running medical image analysis on GridFactory desktop grid.

Frederik Orellana1, Marko Niinimaki, Xin Zhou

  • 1Niels Bohr Institute, Copenhagen University, Denmark.

Studies in Health Technology and Informatics
|July 14, 2009
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A new batch system, GridFactory, was tested for medical image analysis in hospitals. It offers virtualization and firewall benefits, showing satisfactory performance compared to Condor for processing 50,000 anonymized images.

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Area of Science:

  • Medical Image Analysis
  • High-Performance Computing
  • Health Informatics

Background:

  • Hospitals often lack dedicated research computing infrastructure.
  • Medical data privacy regulations restrict data transfer outside hospital networks.
  • Existing batch systems may not meet the specific needs of hospital-based research.

Purpose of the Study:

  • To evaluate a novel batch system, GridFactory, for medical image analysis within a hospital setting.
  • To compare GridFactory's performance against a established system, Condor.
  • To assess the feasibility of using local hospital resources for large-scale medical image processing.

Main Methods:

  • Implementation and testing of the GridFactory batch system on a local grid of 20 desktop computers.
  • Execution of visual feature extraction on 50,000 anonymized medical images.
  • Comparative performance analysis against the Condor batch system under identical conditions.

Main Results:

  • GridFactory demonstrated satisfactory performance for medical image analysis tasks.
  • The system's virtualization support and firewall friendliness were highlighted as key benefits.
  • Successful processing of a large dataset (50,000 images) within the hospital's network.

Conclusions:

  • GridFactory presents a viable solution for establishing research computing facilities in hospitals.
  • The system addresses privacy concerns by enabling local data processing.
  • GridFactory offers advantages over traditional systems like Condor for specific research applications in healthcare.