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  • Research Article
  • Open Access

A Combined Intensity and Gradient-Based Similarity Criterion for Interindividual SPECT Brain Scan Registration

EURASIP Journal on Advances in Signal Processing20032003:967364

https://doi.org/10.1155/S1110865703211239

  • Received: 27 November 2001
  • Published:

Abstract

An evaluation of a new similarity criterion for interindividual image registration is presented. The proposed criterion combines intensity and gradient information from the images to achieve a more robust and accurate registration. It builds on a combination of the normalised mutual information (NMI) cost function and a gradient-weighting function, calculated from gradient magnitude and relative gradient angle values from the images. An investigation was made to determine the best settings for the number of bins in the NMI joint histograms, subsampling, and smoothing of the images prior to the registration. The new method was compared with the NMI and correlation-coefficient (CC) criterions for interindividual SPECT image registration. Two different validation tests were performed, based on the displacement of voxels inside the brain relative to their estimated true positions after registration. The results show that the registration quality was improved when compared with the NMI and CC measures. The actual improvements, in one of the tests, were in the order of 30-40% for the mean voxel displacement error measured within 20 different SPECT images. A conclusion from the studies is that the new similarity measure significantly improves the registration quality, compared with the NMI and CC similarity measures.

Keywords

  • image registration
  • mutual information
  • gradient information

Authors’ Affiliations

(1)
Centre for Image Analysis, Uppsala University, Lägerhyddvägen 3, Uppsala, SE-751 05, Sweden
(2)
Centre for Image Analysis, Uppsala University, Uppsala, Sweden
(3)
Applied Medical Imaging AB, Järpvägen 1, Uppsala, SE-756 53, Sweden

Copyright

© Copyright © 2003 Hindawi Publishing Corporation 2003

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