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Pathological image segmentation for neuroblastoma using the GPU

  • Antonio Ruiz
  • , Jun Kong
  • , Manuel Ujaldon
  • , Kim Boyer
  • , Joel Saltz
  • , Metin Gurcan
  • University of Málaga
  • Ohio State University

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

25 Scopus citations

Abstract

We present a novel use of GPUs (Graphics Processing Units) for the analysis of histopathological images of neuroblastoma, a childhood cancer. Thanks to the advent of modern microscopy scanners, whole-slide histopathological images can now be acquired but the computational costs to analyze these images using sophisticated image analysis algorithms are usually high. In this study, we have implemented previously developed image analysis algorithms using GPUs to exploit their outstanding processing power and memory bandwidth. The resulting GPU code was contrasted and combined with a C++ implementation on a multicore CPU to maximize parallelism on emerging architectures. Our codes were tested on different classes of images, with performance gain factors about 5.6x when the execution time of a Matlab code running on the CPU is compared with a code running jointly on CPU and GPU.

Original languageEnglish
Title of host publication2008 5th IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, Proceedings, ISBI
Pages296-299
Number of pages4
DOIs
StatePublished - 2008
Event2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI - Paris, France
Duration: May 14 2008May 17 2008

Publication series

Name2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Proceedings, ISBI

Conference

Conference2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI
Country/TerritoryFrance
CityParis
Period05/14/0805/17/08

Keywords

  • Computer-aided prognosis
  • Differentiation grading
  • GPU
  • Neuroblastoma
  • Segmentation

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