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Proceedings Paper

Using image synthesis for multi-channel registration of different image modalities
Author(s): Min Chen; Amog Jog; Aaron Carass; Jerry L. Prince
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Paper Abstract

This paper presents a multi-channel approach for performing registration between magnetic resonance (MR) images with different modalities. In general, a multi-channel registration cannot be used when the moving and target images do not have analogous modalities. In this work, we address this limitation by using a random forest regression technique to synthesize the missing modalities from the available ones. This allows a single channel registration between two different modalities to be converted into a multi-channel registration with two mono- modal channels. To validate our approach, two openly available registration algorithms and five cost functions were used to compare the label transfer accuracy of the registration with (and without) our multi-channel synthesis approach. Our results show that the proposed method produced statistically significant improvements in registration accuracy (at an α level of 0.001) for both algorithms and all cost functions when compared to a standard multi-modal registration using the same algorithms with mutual information.

Paper Details

Date Published: 20 March 2015
PDF: 7 pages
Proc. SPIE 9413, Medical Imaging 2015: Image Processing, 94131Q (20 March 2015); doi: 10.1117/12.2082373
Show Author Affiliations
Min Chen, Johns Hopkins Univ. (United States)
Amog Jog, Johns Hopkins Univ. (United States)
Aaron Carass, Johns Hopkins Univ. (United States)
Jerry L. Prince, Johns Hopkins Univ. (United States)

Published in SPIE Proceedings Vol. 9413:
Medical Imaging 2015: Image Processing
Sébastien Ourselin; Martin A. Styner, Editor(s)

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