Biomedical Image Processing / Medical Image Processing
Fateme Nazem; Alireza Ahmadian; Mohammad Javad Abolhasani; Nasim Dadashi; Masoume Gity; Mohammad Bagher Shiran
Volume 5, Issue 4 , June 2011, , Pages 351-358
Abstract
Abstract: Image guided liver surgery based on intra-operative ultrasound images has received much attention in recent years. Using an efficient point-based registration method to improve both the accuracy and computational time for registration of pre-deformation CT liver images to post-deformation Ultrasound ...
Read More
Abstract: Image guided liver surgery based on intra-operative ultrasound images has received much attention in recent years. Using an efficient point-based registration method to improve both the accuracy and computational time for registration of pre-deformation CT liver images to post-deformation Ultrasound images is of great concern during surgical procedure. Although, Iterative Closest Point (ICP) algorithm is widely used in surface-based registration, its performance is strongly dependent on existence of noise and initial alignment. The registration technique based on the Unscented Kalman Filter (UKF) proposed recently can be a solution to overcome to noise and outliers on an incremental registration basis but it suffers from computational complexity. To overcome the limitations of ICP and UKF algorithms we proposed an incremental two-stage registration algorithm based on the combination of ICP and UKF algorithm to update the registration process based on arrival of intra-operative images. The two-stage algorithm is examined on phantom data sets. The results of phantom study confirm that the two-stage algorithm outperforms the accuracy of ICP and UKF by 23% and 13%, respectively and reduces the running time of UKF by 60%.
