Accelerating EPI Distortion Correction by Utilizing a Modern GPU-Based Parallel Computation

Yao Hao Yang, Teng Yi Huang, Fu Nien Wang, Tzu Chao Chuang, Nan Kuei Chen

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


BACKGROUND AND PURPOSE: The combination of phase demodulation and field mapping is a practical method to correct echo planar imaging (EPI) geometric distortion. However, since phase dispersion accumulates in each phase-encoding step, the calculation complexity of phase modulation is Ny-fold higher than conventional image reconstructions. Thus, correcting EPI images via phase demodulation is generally a time-consuming task. METHODS: Parallel computing by employing general-purpose calculations on graphics processing units (GPU) can accelerate scientific computing if the algorithm is parallelized. This study proposes a method that incorporates the GPU-based technique into phase demodulation calculations to reduce computation time. The proposed parallel algorithm was applied to a PROPELLER-EPI diffusion tensor data set. RESULTS: The GPU-based phase demodulation method reduced the EPI distortion correctly, and accelerated the computation. The total reconstruction time of the 16-slice PROPELLER-EPI diffusion tensor images with matrix size of 128 × 128 was reduced from 1,754 seconds to 101 seconds by utilizing the parallelized 4-GPU program. CONCLUSIONS: GPU computing is a promising method to accelerate EPI geometric correction. The resulting reduction in computation time of phase demodulation should accelerate postprocessing for studies performed with EPI, and should effectuate the PROPELLER-EPI technique for clinical practice.

Original languageEnglish (US)
Pages (from-to)202-206
Number of pages5
JournalJournal of Neuroimaging
Issue number2
StatePublished - Apr 2013
Externally publishedYes


  • EPI distortion
  • GPU
  • Parallel computing

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Clinical Neurology


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