A Robust Solution to Multi-modal Image Registration by Combining Mutual Information with Multi-scale Derivatives

In this paper we present a novel method for performing image registration of different modalities. Mutual Information (MI) is an established method for performing such registration. However, it is recognised that standard MI is not without some problems, in particular it does not utilise spatial information within the images. Various modifications have been proposed to resolve this, however these only offer slight improvement to the accuracy of registration. We present Feature Neighbourhood Mutual Information (FNMI) that combines both image structure and spatial neighbourhood information which is efficiently incorporated into Mutual Information by approximating the joint distribution with a covariance matrix (c.f. Russakoff's Regional Mutual Information). Results show that our approach offers a very high level of accuracy that improves greatly on previous methods. In comparison to Regional MI, our method also improves runtime for more demanding registration problems where a higher...

• Type: Conference
• Year: 2009
• Where: MICCAI
• Authors: Philip A. Legg, Paul L. Rosin, A. David Marshall, James E. Morgan
• Keywords: Demanding Registration Problems, Medical Imaging, MICCAI 2009, Neighbourhood Mutual Information, Spatial Neighbourhood Information