Analyzing parallel programming models for magnetic resonance imaging

Forest Danford, Eric Welch, Julio Cárdenas-Ródriguez, Michelle Mills Strout

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


The last several decades have been marked by dramatic increases in the use of diagnostic medical imaging and improvements in the modalities themselves. As such, more data is being generated at an ever increasing rate. However, in the case of Magnetic Resonance Imaging (MRI) analysis and reports remain semi-quantitative, despite reported advantages of quantitative analysis (QA), due to prohibitive execution times. We present a collaborator’s QA algorithm for Dynamic Contrast- Enhanced (DCE) MRI data written in MATLAB as a case study for exploring parallel programming in MATLAB and Julia. Parallelization resulted in a 7.66x speedup in MATLAB and a 72x speedup in Julia. To the best of our knowledge, this comparison of Julia’s performance in a parallel, application-level program is novel. On the basis of these results and our experiences while programming in each language, our collaborator now prototypes in MATLAB and then ports to Julia when performance is critical.

Original languageEnglish (US)
Title of host publicationLanguages and Compilers for Parallel Computing - 29th International Workshop, LCPC 2016, Revised Papers
EditorsChen Ding, John Criswell, Peng Wu
Number of pages15
ISBN (Print)9783319527086
StatePublished - 2017
Event29th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2016 - Rochester, United States
Duration: Sep 28 2016Sep 30 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10136 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference29th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2016
Country/TerritoryUnited States


  • Dynamic Contrast-Enhanced MRI
  • Julia
  • Medical imaging
  • Parallel applications
  • Parallel programming languages

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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