Evaluating similarity measures for brain image registration

Similarity measures for image registration

Normalized similarity measures for medical image registration

Two new similarity measures for rigid image registration, based on the normalization of Jensen’s difference applied to Rényi and Tsallis-Havrda-Charvát entropies, are introduced. One measure is normalized by the first term of Jensen’s difference, which in our proposal coincides with the marginal entropy, and the other by the joint entropy. These measures can be seen as an extension of two measu...

Voxel Similarity Measures for Automated Image Registration

We present the concept of the feature space sequence: 2D distributions of voxel features of two images generated at registration and a sequence of misregistrations. We provide an explanation of the structure seen in these images. Feature space sequences have been generated for a pair of MR image volumes identical apart from the addition of Gaussian noise to one, MR image volumes with and withou...

Image registration: convex weighting functions for histogram-based similarity measures

Recently the entropy-similarity measure has been introduced for the registration of image pairs prior to subtraction in medical imaging e.g. digital subtraction angiography (DSA). The registration is based on motion-vector fields estimated with a template-matching techniques. The entropy is calculated via weighted grey-value histograms of the difference-image template and measures the degree of...

Evaluating Publication Similarity Measures

Publication searching based on keywords provided by users is traditional in digital libraries. While useful in many circumstances, the success of locating related publications via keyword-based searching paradigm is influenced by how users choose their keywords. Example-based searching, where user provides an example publication to locate similar publications, is also becoming commonplace in di...