title: Accelerating image registration of MRI by GPU-based parallel computation.
abstract: Automatic image registration for MRI applications generally requires many iteration loops and is, therefore, a time-consuming task. This drawback prolongs data analysis and delays the workflow of clinical routines. Recent advances in the massively parallel computation of graphic processing units (GPUs) may be a solution to this problem. This study proposes a method to accelerate registration calculations, especially for the popular statistical parametric mapping (SPM) system. This study reimplemented the image registration of SPM system to achieve an approximately 14-fold increase in speed in registering single-modality intrasubject data sets. The proposed program is fully compatible with SPM, allowing the user to simply replace the original image registration library of SPM to gain the benefit of the computation power provided by commodity graphic processors. In conclusion, the GPU computation method is a practical way to accelerate automatic image registration. This technology promises a broader scope of application in the field of image registration.
authors.affiliation: Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei, Taiwan, R.O.C. tyhuang@mail.ntust.edu.tw
authors.forename: Teng-Yi
authors.initials: TY
authors.lastname: Huang
authors.forename: Yu-Wei
authors.initials: YW
authors.lastname: Tang
authors.forename: Shiun-Ying
authors.initials: SY
authors.lastname: Ju
mesh_terms: D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods; D003196:Computer Graphics; D003201:Computers; D001330:Electronic Data Processing; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D012984:Software