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The GPU on biomedical image processing for color and phenotype analysis

  • Antonio Ruiz
  • , Manuel Ujaldón
  • , José Antonio Andrades
  • , José Becerra
  • , Kun Huang
  • , Tony Pan
  • , Joel Saltz
  • University of Málaga
  • Ohio State University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

The computational power and memory bandwidth of graphics processing units (GPUs) have turned them into attractive platforms for general-purpose applications. In this paper, we exploit this power in the context of biomedical image processing by establishing a cooperative environment between the CPU and the GPU. We deal with phenotype and color analysis on a wide variety of microscopic images from studies of cartilage and bone tissue regeneration using stem cells and genetics involving cancer pathology. Both processors are used in parallel to map algorithms for computing color histograms, contour detection using the Canny filter and pattern recognition based on the Hough transform. Task, data and instruction parallelism are exploited in the GPU to accomplish performance gains between 4x and 100x more than the typical CPU code.

Original languageEnglish
Title of host publicationProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Pages1124-1128
Number of pages5
DOIs
StatePublished - 2007
Event7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE - Boston, MA, United States
Duration: Jan 14 2007Jan 17 2007

Publication series

NameProceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

Conference

Conference7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Country/TerritoryUnited States
CityBoston, MA
Period01/14/0701/17/07

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