27 March 2009 Curvelet-based sampling for accurate and efficient multimodal image registration
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Proceedings Volume 7259, Medical Imaging 2009: Image Processing; 72590M (2009) https://doi.org/10.1117/12.810695
Event: SPIE Medical Imaging, 2009, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
We present a new non-uniform adaptive sampling method for the estimation of mutual information in multi-modal image registration. The method uses the Fast Discrete Curvelet Transform to identify regions along anatomical curves on which the mutual information is computed. Its main advantages of over other non-uniform sampling schemes are that it captures the most informative regions, that it is invariant to feature shapes, orientations, and sizes, that it is efficient, and that it yields accurate results. Extensive evaluation on 20 validated clinical brain CT images to Proton Density (PD) and T1 and T2-weighted MRI images from the public RIRE database show the effectiveness of our method. Rigid registration accuracy measured at 10 clinical targets and compared to ground truth measurements yield a mean target registration error of 0.68mm(std=0.4mm) for CT-PD and 0.82mm(std=0.43mm) for CT-T2. This is 0.3mm (1mm) more accurate in the average (worst) case than five existing sampling methods. Our method has the lowest registration errors recorded to date for the registration of CT-PD and CT-T2 images in the RIRE website when compared to methods that were tested on at least three patient datasets.
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M. N. Safran, M. N. Safran, M. Freiman, M. Freiman, M. Werman, M. Werman, L. Joskowicz, L. Joskowicz, } "Curvelet-based sampling for accurate and efficient multimodal image registration", Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72590M (27 March 2009); doi: 10.1117/12.810695; https://doi.org/10.1117/12.810695
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