TY - GEN
T1 - Analyzing parallel programming models for magnetic resonance imaging
AU - Danford, Forest
AU - Welch, Eric
AU - Cárdenas-Ródriguez, Julio
AU - Strout, Michelle Mills
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Dynamic Contrast-Enhanced MRI
KW - Julia
KW - MATLAB
KW - Medical imaging
KW - Parallel applications
KW - Parallel programming languages
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U2 - 10.1007/978-3-319-52709-3_15
DO - 10.1007/978-3-319-52709-3_15
M3 - Conference contribution
AN - SCOPUS:85011419007
SN - 9783319527086
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 188
EP - 202
BT - Languages and Compilers for Parallel Computing - 29th International Workshop, LCPC 2016, Revised Papers
A2 - Ding, Chen
A2 - Criswell, John
A2 - Wu, Peng
PB - Springer-Verlag
T2 - 29th International Workshop on Languages and Compilers for Parallel Computing, LCPC 2016
Y2 - 28 September 2016 through 30 September 2016
ER -