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Multichannel Image Registration by Feature-Based Information Fusion

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2 Author(s)
Yang Li ; Section of Biomedical Image Analysis (SBIA), Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA ; Ragini Verma

This paper proposes a novel nonrigid inter-subject multichannel image registration method which combines information from different modalities/channels to produce a unified joint registration. Multichannel images are created using co-registered multimodality images of the same subject to utilize information across modalities comprehensively. Contrary to the existing methods which combine the information at the image/intensity level, the proposed method uses feature-level information fusion method to spatio-adaptively combine the complementary information from different modalities that characterize different tissue types, through Gabor wavelets transformation and Independent Component Analysis (ICA), to produce a robust inter-subject registration. Experiments on both simulated and real multichannel images illustrate the applicability and robustness of the proposed registration method that combines information across modalities. This inter-subject registration is expected to pave the way for subsequent unified population-based multichannel studies.

Published in:

IEEE Transactions on Medical Imaging  (Volume:30 ,  Issue: 3 )