Parallel Adaptive Estimation of Hip Range of Motion for Total Hip Replacement Surgery

Yasuhiro KAWASAKI  Fumihiko INO  Yoshinobu SATO  Shinichi TAMURA  Kenichi HAGIHARA  

IEICE TRANSACTIONS on Information and Systems   Vol.E90-D   No.1   pp.30-39
Publication Date: 2007/01/01
Online ISSN: 1745-1361
Print ISSN: 0916-8532
Type of Manuscript: Special Section PAPER (Special Section on Parallel/Distributed Processing and Systems)
Category: Parallel Image Processing
range of motion estimation,  adaptive mesh refinement,  cluster computing,  medical image processing,  computer assisted surgery,  

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This paper presents the design and implementation of a hip range of motion (ROM) estimation method that is capable of fine-grained estimation during total hip replacement (THR) surgery. Our method is based on two acceleration strategies: (1) adaptive mesh refinement (AMR) for complexity reduction and (2) parallelization for further acceleration. On the assumption that the hip ROM is a single closed region, the AMR strategy reduces the complexity for N N N stance configurations from O(N3) to O(ND), where 2≤D≤3 and D is a data-dependent value that can be approximated by 2 in most cases. The parallelization strategy employs the master-worker paradigm with multiple task queues, reducing synchronization between processors with load balancing. The experimental results indicate that the implementation on a cluster of 64 PCs completes estimation of 360360180 stance configurations in 20 seconds, playing a key role in selecting and aligning the optimal combination of artificial joint components during THR surgery.