A new divergence measure for medical image registration

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 Kullba...

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Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society. - 1992. - 16(2007), 4 vom: 19. Apr., Seite 957-66
1. Verfasser: Martin, Stefan (VerfasserIn)
Weitere Verfasser: Durrani, Tariq S
Format: Aufsatz
Sprache:English
Veröffentlicht: 2007
Zugriff auf das übergeordnete Werk:IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
Schlagworte:Evaluation Study Journal Article Research Support, N.I.H., Extramural Validation Study
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520 |a 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 Iinfinity, 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 
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650 4 |a Validation Study 
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