NDLI: Mutual information extremal optimization for multimodal medical image registration

Content Provider	IEEE Xplore Digital Library
Author	Sanchez, P.P.C. Ayala, H.L. Schaerer, C.E.
Copyright Year	2014
Abstract	In this paper it is considered the image registration (IR) between medical images of computed tomography and magnetic resonance. Our approach formulates the IR as an optimization problem where mutual information cost function is used as a similarity metric (cost function). The Extremal Optimization algorithm is implemented as the optimizer. The numerical results are contrasted against two state of the art optimization algorithms for this kind of problems (being one deterministic and another evolutionary). Our approach is competitive with the deterministic algorithm in accuracy and with the evolutionary algorithms in computational cost. The qualitative results are quite satisfactory with a 83 % of success, whilst the quantitative results present an average error of 0.36mm with registrations of CT with proton density MR. The results show that the proposal is useful for multimodal registrations.
Starting Page	1
Ending Page	12
File Size	1092493
Page Count	12
File Format	PDF
ISBN	9781479961306
DOI	10.1109/CLEI.2014.6965101
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-09-15
Publisher Place	Uruguay
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image registration Three-dimensional displays Medical images registration Computed tomography Extremal optimization Educational institutions Optimization Mutual information Biomedical imaging
Content Type	Text
Resource Type	Article

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