A New Divergence Measure for Medical Image Registration

Author

Martin, Stefan ; Durrani, Tariq S.

Author_Institution

Electron. & Electr. Eng. Dept., Univ. of Strathclyde, Glasgow

Volume

16

Issue

4

fYear

2007

fDate

4/1/2007 12:00:00 AM

Firstpage

957

Lastpage

966

Abstract

A new type of divergence measure for the registration of medical images is introduced that exploits the properties of the modified Bessel functions of the second kind. The properties of the proposed divergence coefficient are analysed and compared with those of the classic measures, including Kullback-Leibler, Renyi, and I_alpha divergences. To ensure its effectiveness and widespread applicability to any arbitrary set of data types, the performance of the new measure is analysed for Gaussian, exponential, and other advanced probability density functions. The results verify its robustness. Finally, the new divergence measure is used in the registration of CT to MR medical images to validate the improvement in registration accuracy

Keywords

Bessel functions; Gaussian processes; biomedical MRI; computerised tomography; image registration; medical image processing; CT medical images; Gaussian functions; MR medical images; advanced probability density functions; exponential functions; medical image registration; modified Bessel functions; Biomedical imaging; Computed tomography; Density measurement; Image registration; Mutual information; Particle measurements; Performance analysis; Probability density function; Probability distribution; Robustness; Divergence measure; image registration; modified Bessel function; Algorithms; Image Enhancement; Image Interpretation, Computer-Assisted; Magnetic Resonance Imaging; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Subtraction Technique; Tomography, X-Ray Computed;

fLanguage

English

Journal_Title

Image Processing, IEEE Transactions on

Publisher

ieee

ISSN

1057-7149

Type

jour

DOI

10.1109/TIP.2007.891772

Filename

4130432