A minimum description length objective function for groupwise non-rigid image registration
Image and Vision Computing
Polynomial intensity correction for multimodal image registration
ISBI'09 Proceedings of the Sixth IEEE international conference on Symposium on Biomedical Imaging: From Nano to Macro
Efficient population registration of 3d data
CVBIA'05 Proceedings of the First international conference on Computer Vision for Biomedical Image Applications
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This work presents a group-wise motion correction method to align a series of brain perfusion scans simultaneously. The cost function used in this group-wise registration technique is derived from the total quadratic variation of image intensity. Optimization of the total quadratic variation with respect to rigid registration parameters is a least squares problem and can be efficiently solved by the Levenberg-Marquardt method. The group-wise registration error was quantitatively measured by comparing the registration results with ground truths that were obtained by applying artificial motions to a series of 50 brain perfusion scans. The average registration error is 0.869 ± 0.579mm, and the maximum error is 3.550 mm. The capture range and robustness was also tested by 11 MR brain perfusion scans with large patient motion. The results demonstrated a high level of accuracy and robustness achieved by the group-wise registration.