Automatic 4-D registration in dynamic MR renography based on over-complete dyadic wavelet and Fourier transforms.
Dynamic contrast-enhanced 4-D MR renography has the potential for broad clinical applications, but suffers from respiratory motion that limits analysis and interpretation. Since each examination yields at least over 10-20 serial 3-D images of the abdomen, manual registration is prohibitively labor-intensive. Besides in-plane motion and translation, out-of-plane motion and rotation are observed in the image series. In this paper, a novel robust and automated technique for removing out-of-plane translation and rotation with sub-voxel accuracy in 4-D dynamic MR images is presented. The method was evaluated on simulated motion data derived directly from a clinical patient's data. The method was also tested on 24 clinical patient kidney data sets. Registration results were compared with a mutual information method, in which differences between manually co-registered time-intensity curves and tested time-intensity curves were compared. Evaluation results showed that our method agreed well with these ground truth data.
Song
Ting
T
Department of Biomedical Engineering, Columbia University, New York, NY, USA. ts2060@columbia.edu
Lee
Vivian S
VS
Rusinek
Henry
H
Kaur
Manmeen
M
Laine
Andrew F
AF