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A much-used measure for registration of three-dimensional medical images is mutual information, which originates from information theory. However, information theory offers many more measures that may be suitable for image registration. Such measures denote the divergence of the joint grey value distribution of two images from the joint distribution for complete independence of the images. This paper compares the performance of mutual information as a registration measure with that of other information measures. The measures are applied to rigid registration of clinical PET/MR and MR/CT images, for 35 and 41 image pairs respectively. An accurate gold standard transformation is available for the images, based on implanted markers. Both registration performance and accuracy of the measures are studied. The results indicate that some information measures perform very poorly for the chosen registration problems, yielding many misregistrations, even when using a good starting estimate. Other measures, however, were shown to produce significantly more accurate results than mutual information.

<title><emph type="1">f</emph>-information measures in medical image registration</title>