Information Theoretic Similarity Measures in Non-rigid Registration
- 1 January 2003
- book chapter
- conference paper
- Published by Springer Science and Business Media LLC in Lecture Notes in Computer Science
- Vol. 18, 378-387
- https://doi.org/10.1007/978-3-540-45087-0_32
Abstract
Mutual Information (MI) and Normalised Mutual Information (NMI) have enjoyed success as image similarity measures in medical image registration. More recently, they have been used for non-rigid registration, most often evaluated empirically as functions of changing registration parameter. In this paper we present expressions derived from intensity histogram representations of these measures, for their change in response to a local perturbation of a deformation field linking two images. These expressions give some insight into the operation of NMI in registration and are implemented as driving forces within a fluid registration framework. The performance of the measures is tested on publicly available simulated multi-spectral MR brain images.Keywords
This publication has 14 references indexed in Scilit:
- A Viscous Fluid Model for Multimodal Non-rigid Image Registration Using Mutual InformationLecture Notes in Computer Science, 2002
- Comparative evaluation of multiresolution optimization strategies for multimodality image registration by maximization of mutual informationMedical Image Analysis, 1999
- Towards a Better Comprehension of Similarity Measures Used in Medical Image RegistrationLecture Notes in Computer Science, 1999
- MRI simulation-based evaluation of image-processing and classification methodsIEEE Transactions on Medical Imaging, 1999
- An overlap invariant entropy measure of 3D medical image alignmentPattern Recognition, 1999
- Modeling Brain Deformations in Alzheimer Disease by Fluid Registration of Serial 3D MR ImagesJournal of Computer Assisted Tomography, 1998
- Multimodality image registration by maximization of mutual informationIEEE Transactions on Medical Imaging, 1997
- Multi-modal volume registration by maximization of mutual informationMedical Image Analysis, 1996
- Deformable templates using large deformation kinematicsIEEE Transactions on Image Processing, 1996
- Alignment by Maximization of Mutual InformationPublished by Defense Technical Information Center (DTIC) ,1995