A point based non-rigid registration for tumor resection using IMRI

Authors:
Yixun Liu;Chengjun Yao;LiangFu Zhou;Nikos Chrisochoides
Affiliations:
Department of Computer Science, College of William and Mary, Williamsburg;Neurosurgery, Huashan Hospital, Shanghai, China;Neurosurgery, Huashan Hospital, Shanghai, China;Department of Computer Science, College of William and Mary, Williamsburg
Venue:
ISBI'10 Proceedings of the 2010 IEEE international conference on Biomedical imaging: from nano to Macro
Year:
2010

Citing 1
Cited 2

A new point matching algorithm for non-rigid registration

Computer Vision and Image Understanding - Special issue on nonrigid image registration

High quality real-time image-to-mesh conversion for finite element simulations

Proceedings of the 27th international ACM conference on International conference on supercomputing
High quality real-time Image-to-Mesh conversion for finite element simulations

Journal of Parallel and Distributed Computing

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper presents a novel feature point based non-rigid registration of preoperative MRI with resected intra-operative MRI (iMRI) to compensate for brain shift during tumor resection. The registration is formulated as a three variables (Correspondence,Deformation Field and Resection Region) functional minimization problem. We solve this problem by means of a nested Expectation and Maximization (EM) framework where: (1) the inner EM loop computes the Correspondence and Deformation Field by iteratively rejecting point outliers and (2) the outer EM loop computes the Resection Region by iteratively rejecting resected elements. Our preliminary data from both synthetic and real brain MRI show the effectiveness of this method to handle tumor resection. The results of the registration in the vicinity of the tumor resection is on average, 16 times more accurate than the results from rigid registration.