2009 | OriginalPaper | Buchkapitel
Hybrid Spline-Based Multimodal Registration Using Local Measures for Joint Entropy and Mutual Information
verfasst von : Andreas Biesdorf, Stefan Wörz, Hans-Jürgen Kaiser, Christoph Stippich, Karl Rohr
Erschienen in: Medical Image Computing and Computer-Assisted Intervention – MICCAI 2009
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
We introduce a new hybrid approach for spline-based elastic registration of multimodal medical images. The approach uses point landmarks as well as intensity information based on local analytic measures for joint entropy and mutual information. The information-theoretic similarity measures are computationally efficient and can be optimized independently for each voxel. We have applied our approach to synthetic images, brain phantom images, as well as clinically relevant multimodal medical images. We also compared our measures with previous measures.