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《Journal of Data Acquisition and Processing》 2018-02
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Medical Image Registration Based on Mutual Information Entropy Combined with Edge Correlation Feature

Wei Benzheng;Gan Jie;Yin Yilong;College of Science and Technology,Shandong University of Traditional Chinese Medicine;Computational Medicine Lab,Shandong University of Traditional Chinese Medicine;Department of Radiology,Second Affiliated Hospital of Shandong University of Traditional Chinese Medicine;School of Computer Science and Technology,Shandong University;  
Image registration is a valuable technique for medical diagnosis and treatment.Due to the inferiority of image registration using maximum mutual information,a new hybrid method of multimodality medical image registration based on mutual information of spatial information is proposed.The new measure that combines mutual information,spatial information and feature characteristics,is proposed.Edge points are used as features and obtained from a morphology gradient detector.Feature characteristics like location,edge strength and orientation are taken into account to compute a joint probability distribution of corresponding edge points in two images.Mutual information based on this function is minimized to find the best alignment parameters.Finally,the translation parameters are calculated by using a gradient descent algorithm.The experimental results demonstrate the high validation precision and excellent accelerating capability of the algorithm.
【Fund】: 国家自然科学基金(U1201258 61572300)资助项目;; 山东省自然科学基金(ZR2015FM010)资助项目;; 山东高校科技计划(J15LN20)资助项目;; 山东省中医药科技发展计划(2015-026)资助项目
【CateGory Index】: TP391.41
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