Abstract: In order to reduce local maximum and misregistration of mutual information in medical image registration，three information measures based on generalized entropy instead of the Shannon entropy，named as FRI-alpha，SRI-alpha and GMI-t information measures，are proposed.The convergence width and radius are used for evaluating the measure convergence.The computing time，convergence and accuracy are studied by applying these measures to rigid registration of Computed Tomography（CT）/Magnetic Resonance（MR） and MR-T1/T2 simulated images.The results of tests show that the generalized entropy measures outperform normalized mutual information in convergence performance，without compromising computational speed and registration accuracy.