A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use.
IEEE TRANS MED IMAGING
(278-0062 (Print), 8)
1058 - 1066.
Two-dimensional (2-D)-to-three-dimensional (3-D) registration can improve visualization which may aid minimally invasive neurointerventions. Using clinical and phantom studies, two state-of-the-art approaches to rigid registration are compared quantitatively: an intensity-based algorithm using the gradient difference similarity measure; and an iterative closest point (ICP)-based algorithm. The gradient difference approach was found to be more accurate, with an average registration accuracy of 1.7 mm for clinical data, compared to the ICP-based algorithm with an average accuracy of 2.8 mm. In phantom studies, the ICP-based algorithm proved more reliable, but with more complicated clinical data, the gradient difference algorithm was more robust. Average computation time for the ICP-based algorithm was 20 s per registration, compared with 14 min and 50 s for the gradient difference algorithm
|Title:||A comparison of a similarity-based and a feature-based 2-D-3-D registration method for neurointerventional use|
|Additional information:||DA - 20050811|
|Keywords:||Algorithms, Arteriovenous Malformations, Artificial Intelligence, Cluster Analysis, Comparative Study, diagnosis, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Intracranial Aneurysm, methods, Neuronavigation, Pattern Recognition, Automated, Reproducibility of Results, Research Support, Non-U.S.Gov't, Sensitivity and Specificity, Subtraction Technique|
|UCL classification:||UCL > School of BEAMS > Faculty of Engineering Science > Medical Physics and Bioengineering|
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