A new divergence measure for medical image registration

S. Martin, T.S. Durrani

Research output: Contribution to journalArticle

12 Citations (Scopus)

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 Ialpha 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
Original languageEnglish
Pages (from-to)957-966
Number of pages9
JournalIEEE Transactions on Image Processing
Volume16
Issue number4
DOIs
Publication statusPublished - Apr 2007

Keywords

  • divergence measure
  • image registration
  • modifiedBessel function

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