Analyzing Parallel Programming Models for Magnetic Resonance Imaging

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.