HyperLink   IMPATIENT MRI: Illinois Massively Parallel Acceleration Toolkit for Image Reconstruction with ENhanced Throughput in MRI
Publication Year:
  Xiao-Long Wu, Jiading Gai, Fan Lam, Maojing Fu, Justin P. Haldar, Yue Zhuo, Zhi-Pei Liang, Wen-mei Hwu, Bradley P. Sutton
  Proceedings of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2011

Significant progress has been made in optimizing imaging trajectories and reconstruction approaches for a variety of MRI application areas. Often these acquisitions result in high resolution 2D or 3D data acquired with non-Cartesian trajectories that have been significantly under-sampled. Image reconstruction is then performed either in unacceptably long times or with highly optimized code that includes several approximations and interpolat ion steps in order to keep the reconstruction time low. In this work, we introduce the Illinois Massively Parallel Acceleration Toolkit for Image reconstruction with ENhanced Throughput in MRI(IMPATIENT MRI) package to speed image reconstruction to acceptable times while still taking advantage of a variety of advanced image acquisitions and reconstruction techniques. We provide an open source, highly optimized implementation on graphics processing units (GPUs) whi ch allow for massively aparallel computation to greatly reduce image reconstruction times.