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Tools for efficient subsetting and pipelined processing of large scale, distributed biomedical image data

  • Matheus Ribeiro
  • , Tahsin Kurc
  • , Tony Pan
  • , Kun Huang
  • , Umit Catalyurek
  • , Xi Zhang
  • , Steve Langella
  • , Shannon Hastings
  • , Scott Oster
  • , Renato Ferreira
  • , Joel Saltz
  • Universidade Federal de Minas Gerais
  • Ohio State University

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

This paper presents a suite of tools and techniques for efficient storage, retrieval, and processing of multi-dimensional, multi-resolution biomedical image datasets on parallel and distributed storage systems. We present the implementation of various services using these tools. We demonstrate the coordinated use of the services to support biomedical image analysis applications that access subsets of terabyte scale multi-resolution datasets and that make use of a variety of image processing algorithms on large-scale digitized microscopy slides.

Original languageEnglish
Pages (from-to)403-422
Number of pages20
JournalAdvances in Parallel Computing
Volume14
Issue numberC
DOIs
StatePublished - 2005

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