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Computers in biology and medicine v.95, 2018년, pp.1 - 12   SCI SCIE SCOPUS
본 등재정보는 저널의 등재정보를 참고하여 보여주는 베타서비스로 정확한 논문의 등재여부는 등재기관에 확인하시기 바랍니다.

QR-decomposition based SENSE reconstruction using parallel architecture

Ullah, Irfan (Corresponding Author. Room 402 Cubator 1ne, Medical Image Processing Research Group Lab, Department of Electrical Engineering, COMSATS Institute of Information Technology, Islamabad, Pakistan. ) ; Nisar, Habab ; Raza, Haseeb ; Qasim, Malik ; Inam, Omair ; Omer, Hammad ;
  • 초록  

    Abstract Magnetic Resonance Imaging (MRI) is a powerful medical imaging technique that provides essential clinical information about the human body. One major limitation of MRI is its long scan time. Implementation of advance MRI algorithms on a parallel architecture (to exploit inherent parallelism) has a great potential to reduce the scan time. Sensitivity Encoding (SENSE) is a Parallel Magnetic Resonance Imaging (pMRI) algorithm that utilizes receiver coil sensitivities to reconstruct MR images from the acquired under-sampled k -space data. At the heart of SENSE lies inversion of a rectangular encoding matrix. This work presents a novel implementation of GPU based SENSE algorithm, which employs QR decomposition for the inversion of the rectangular encoding matrix. For a fair comparison, the performance of the proposed GPU based SENSE reconstruction is evaluated against single and multicore CPU using openMP. Several experiments against various acceleration factors (AFs) are performed using multichannel (8, 12 and 30) phantom and in-vivo human head and cardiac datasets. Experimental results show that GPU significantly reduces the computation time of SENSE reconstruction as compared to multi-core CPU (approximately 12x speedup) and single-core CPU (approximately 53x speedup) without any degradation in the quality of the reconstructed images. Highlights QR decomposition based SENSE algorithm for MR image reconstruction is proposed. Proposed method is successfully implemented on CPU (C,OpenMP) and GPU (CUDA). GPU implementation successfully exploits the inherent parallelism of QR based SENSE. GPU gives (up to) 12x speedup as compare to multi core CPU implementation. GPU gives (up to) 53x speedup as compare to single core CPU implementation.


  • 주제어

    Parallel computation .   MRI .   GPU .   SENSE .   QR-Decomposition .   pMRI .   OpenMP.  

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