Spatial Mutual Information as Similarity Measure for 3-D Brain Image Registration

IEEE Journal of Translational Engineering in Health and Medicine

卷:2

Qolamreza R. Razlighi¹  Nasser Kehtarnavaz² 

[1] Department of Biomedical Engineering and Neurology, Columbia University, New York, NY, USA;

[2] Department of Electrical Engineering, University of Texas at Dallas, Richardson, TX, USA;

关键词: Spatial mutual information;    spatially dependent similarity measures;    brain image registration;    spatial entropy;   

DOI  :  10.1109/JTEHM.2014.2299280

来源: DOAJ

【 摘 要 】

Information theoretic-based similarity measures, in particular mutual information, are widely used for intermodal/intersubject 3-D brain image registration. However, conventional mutual information does not consider spatial dependency between adjacent voxels in images, thus reducing its efficacy as a similarity measure in image registration. This paper first presents a review of the existing attempts to incorporate spatial dependency into the computation of mutual information (MI). Then, a recently introduced spatially dependent similarity measure, named spatial MI, is extended to 3-D brain image registration. This extension also eliminates its artifact for translational misregistration. Finally, the effectiveness of the proposed 3-D spatial MI as a similarity measure is compared with three existing MI measures by applying controlled levels of noise degradation to 3-D simulated brain images.

【 授权许可】

Unknown