A "twisting and bending" model-based nonrigid image registration technique for 3-D ultrasound carotid images.
Atherosclerosis at the carotid bifurcation resulting in cerebral emboli is a major cause of ischemic stroke. Most strokes associated with carotid atherosclerosis can be prevented by lifestyle/dietary changes and pharmacological treatments if identified early by monitoring carotid plaque changes. Registration of 3-D ultrasound (US) images of carotid plaque obtained at different time points is essential for sensitive monitoring of plaque changes in volume and surface morphology. This registration technique should be nonrigid, since different head positions during image acquisition sessions cause relative bending and torsion in the neck, producing nonlinear deformations between the images. We modeled the movement of the neck using a "twisting and bending" model with only six parameters for nonrigid registration. We evaluated the algorithm using 3-D US carotid images acquired at two different head positions to simulate images acquired at different times. We calculated the mean registration error (MRE) between the segmented vessel surfaces in the target image and the registered image using a distance-based error metric after applying our "twisting and bending" model-based nonrigid registration algorithm. We achieved an average registration error of 0.80 +/-0.26 mm using our nonrigid registration technique, which was a significant improvement in registration accuracy over rigid registration, even with reduced degrees-of-freedom compared to the other nonrigid registration algorithms.
Nanayakkara
Nuwan D
ND
Imaging Research Laboratories, Robarts Research Institute and Graduate Program in Biomedical Engineering, The University of Western Ontario, London, ON N6A5K8, Canada. nnanayak@uwo.ca
Chiu
Bernard
B
Samani
Abbas
A
Spence
J David
JD
Samarabandu
Jagath
J
Fenster
Aaron
A
D000465:Algorithms; D001185:Artificial Intelligence; D002339:Carotid Arteries / Q000000981:diagnostic imaging*; D002340:Carotid Artery Diseases / Q000000981:diagnostic imaging*; D003198:Computer Simulation; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008955:Models, Cardiovascular; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D014463:Ultrasonography