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High Performance Computing Techniques for Scaling Image Analysis Workflows

  • Patrick M. Widener
  • Tahsin Kurc
  • Wenjin Chen
  • Fusheng Wang
  • Lin Yang
  • Jun Hu
  • Vijay Kumar
  • Vicky Chu
  • Lee Cooper
  • Jun Kong
  • Ashish Sharma
  • Tony Pan
  • Joel H. Saltz
  • David J. Foran
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7134)

Abstract

Biomedical images are intrinsically complex with each domain and modality often requiring specialized knowledge to accurately render diagnosis and plan treatment. A general software framework that provides access to high-performance resources can make possible high-throughput investigations of micro-scale features as well as algorithm design, development and evaluation. In this paper we describe the requirements and challenges of supporting microscopy analyses of large datasets of high-resolution biomedical images. We present high-performance computing approaches for storage and retrieval of image data, image processing, and management of analysis results for additional explorations. Lastly, we describe issues surrounding the use of high performance computing for scaling image analysis workflows.

Keywords

High Performance Computing Database Management System Slave Node Virtual Microscopy Data Access Pattern 
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 2012

Authors and Affiliations

  • Patrick M. Widener
    • 1
  • Tahsin Kurc
    • 1
  • Wenjin Chen
    • 2
  • Fusheng Wang
    • 1
  • Lin Yang
    • 2
  • Jun Hu
    • 2
  • Vijay Kumar
    • 3
  • Vicky Chu
    • 2
  • Lee Cooper
    • 1
  • Jun Kong
    • 1
  • Ashish Sharma
    • 1
  • Tony Pan
    • 1
  • Joel H. Saltz
    • 1
  • David J. Foran
    • 2
  1. 1.Center for Comprehensive InformaticsEmory UniversityUSA
  2. 2.Center for Biomedical Imaging & InformaticsUMDNJ-Robert Wood Johnson Medical SchoolUSA
  3. 3.Department of Computer Science and EngineeringOhio State UniversityUSA

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