PublicationDetail

Chair for Computer Aided Medical Procedures & Augmented Reality
Lehrstuhl für Informatikanwendungen in der Medizin & Augmented Reality

THIS WEBPAGE IS DEPRECATED - please visit our new website

O. Pauly, N. Padoy, H. Poppert, I. Esposito, H-H. Eckstein, N. Navab
Towards Application-specific Multi-modal Similarity Measures: a Regression Approach.
MICCAI Workshop on Probabilistic Models in Medical Image Analysis (PMMIA), London, UK, September 2009. (bib)

In multi-modal registration, similarity measures based on intensity statistics are the current standard for aligning medical images acquired with different imaging systems. In fact, the statistical relationship relating the intensities of two multi-modal images is constrained by the application, defined in terms of anatomy and imaging modalities. In this paper, we present the benefits of exploiting application-specific prior information contained in one single pair of registered images. By varying the relative transformation parameters of registered images around the ground truth position, we explore the manifold described by their joint intensity distributions. An adapted measure is fitted using support vector regression on the training set formed by points on the manifold and their respective geometric errors. Experiments are conducted on two different pairs of modalities, MR-T1/MR-TOF and MR-T1/SPECT. We compare the results with those obtained using mutual information and Kullback-Leibler distance. Experimental results show that the proposed method presents a promising alternative for multi-modal registration.
This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each authors copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.



Edit | Attach | Refresh | Diffs | More | Revision r1.13 - 30 Jan 2019 - 15:16 - LeslieCasas

Lehrstuhl für Computer Aided Medical Procedures & Augmented Reality    rss.gif