Parallel computation of mutual information on the GPU with application to real-time registration of 3D medical images

  • Authors:
  • Ramtin Shams;Parastoo Sadeghi;Rodney Kennedy;Richard Hartley

  • Affiliations:
  • College of Engineering and Computer Science (CECS), The Australian National University, Canberra, ACT 0200, Australia;College of Engineering and Computer Science (CECS), The Australian National University, Canberra, ACT 0200, Australia;College of Engineering and Computer Science (CECS), The Australian National University, Canberra, ACT 0200, Australia;College of Engineering and Computer Science (CECS), The Australian National University, Canberra, ACT 0200, Australia

  • Venue:
  • Computer Methods and Programs in Biomedicine
  • Year:
  • 2010

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Abstract

Due to processing constraints, automatic image-based registration of medical images has been largely used as a pre-operative tool. We propose a novel method named sort and count for efficient parallelization of mutual information (MI) computation designed for massively multi-processing architectures. Combined with a parallel transformation implementation and an improved optimization algorithm, our method achieves real-time (less than 1s) rigid registration of 3D medical images using a commodity graphics processing unit (GPU). This represents a more than 50-fold improvement over a standard implementation on a CPU. Real-time registration opens new possibilities for development of improved and interactive intraoperative tools that can be used for enhanced visualization and navigation during an intervention.