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Local non-rigid image registration using mutual information

Fookes, Clinton B. & Maeder, Anthony J. (2003) Local non-rigid image registration using mutual information. In 16th International Conference on Vision Interface VI 2003, June 11-13, 2003, Halifax, Canada.

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Abstract

Recently there has emerged a need to compute multimodal non-rigid registrations in a lot of clinical applications. To date, the viscous fluid algorithm is perhaps the most adept method at recovering large local misregistrations that exist between two images. However, this model can only be used on images from the same modality as it assumes similar intensity values between images. This paper presents a solution to this problem by proposing a hybrid non-rigid registration using the viscous fluid algorithm and mutual information (MI). The MI is incorporated via the use of a block matching procedure to generate a sparse deformation field which drives the viscous fluid algorithm. This algorithmis compared to two other popular local registration approaches, namely Gaussian convolution and the thin-plate spline warp. Results showthat the thin-plate splinewarp and the MI-Fluid approach produce comparable results. However, Gaussian convolution is the superior choice, especially in controlled environments.

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ID Code: 17929
Item Type: Conference Paper
Keywords: Non-rigid image registration, Mutual Information, Viscous Fluid
Subjects: Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Computer Vision (080104)
Australian and New Zealand Standard Research Classification > INFORMATION AND COMPUTING SCIENCES (080000) > ARTIFICIAL INTELLIGENCE AND IMAGE PROCESSING (080100) > Image Processing (080106)
Divisions: Past > QUT Faculties & Divisions > Faculty of Built Environment and Engineering
Past > Schools > School of Engineering Systems
Copyright Owner: Copyright 2003 (please consult author)
Deposited On: 17 Feb 2009 15:50
Last Modified: 09 Jun 2010 23:23

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