An Improved SIFT Algorithm and Its Application in Medical Image Registration
Xiaoyang Huang · Journal of Xiamen University · 2010
Feature extraction is the basis of medical image registration.The accuracy of feature points directly affects matching result.It often use manpower to do feature extraction at present,but the accuracy is poor and the workload is heavy.The features extracted with SIFT are invariant to image scale and rotation,and provide robust matching.SIFT algorithm has been widely used in image registration.As the SIFT algorithm is very strict about matching condition,the number of feature points often can not meet the needs of medical image registration,and there are some false matches to a certain extent.In order to increase the number of feature points and improve the matching accuracy,the Euclid distance has been adopted to determine the similarity between feature points and low contrast points have been retained according to the characteristics of medical images.The experiment results demonstrate the effectiveness of this method.