Document Detail

Gauss-Newton inspired preconditioned optimization in large deformation diffeomorphic metric mapping.
MedLine Citation:
PMID:  25254606     Owner:  NLM     Status:  In-Data-Review    
In this work, we propose a novel preconditioned optimization method in the paradigm of Large Deformation Diffeomorphic Metric Mapping (LDDMM). The preconditioned update scheme is formulated for the non-stationary and the stationary parameterizations of diffeomorphisms, yielding three different LDDMM methods. The preconditioning matrices are inspired in the Hessian approximation used in Gauss-Newton method. The derivatives are computed using Frechet differentials. Thus, optimization is performed in a Sobolev space, in contrast to optimization in L(2) commonly used in non-rigid registration literature. The proposed LDDMM methods have been evaluated and compared with their respective implementations of gradient descent optimization. Evaluation has been performed using real and simulated images from the Non-rigid Image Registration Evaluation Project (NIREP). The experiments conducted in this work reported that our preconditioned LDDMM methods achieved a performance similar or superior to well-established-in-literature gradient descent non-stationary LDDMM in the great majority of cases. Moreover, preconditioned optimization showed a substantial reduction in the execution time with an affordable increase of the memory usage per iteration. Additional experiments reported that optimization using Frechet differentials should be preferable to optimization using L(2) differentials.
Monica Hernandez
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Publication Detail:
Type:  Journal Article     Date:  2014-09-25
Journal Detail:
Title:  Physics in medicine and biology     Volume:  59     ISSN:  1361-6560     ISO Abbreviation:  Phys Med Biol     Publication Date:  2014 Oct 
Date Detail:
Created Date:  2014-09-26     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  0401220     Medline TA:  Phys Med Biol     Country:  England    
Other Details:
Languages:  eng     Pagination:  6085-115     Citation Subset:  IM    
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