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

Yasuhiro KAWASAKI  Fumihiko INO  Yoshinobu SATO  Shinichi TAMURA  Kenichi HAGIHARA  

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

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Summary: 
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.