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Bi-modal Non-rigid Registration of Brain MRI Data Based on Deconvolution of Joint Statistics

机译:基于联合统计的折折叠的脑MRI数据双型非刚性注册

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Images of different contrasts in MRI can contain complementary information and can highlight different tissue types. Such datasets often need to be co-registered for any further processing. A novel and effective non-rigid registration method based on the restoration of the joint statistics of pairs of such images is proposed. The registration is performed with the deconvolution of the joint statistics and then with the enforcement of the deconvolved statistics back to the spatial domain to form a preliminary registration. The spatial transformation is also regularized with Gaussian spatial smoothing. The registration method has been compared to B-Splines and validated with a simulated Shepp-Logan phantom, with the BrainWeb phantom, and with real datasets. Improved results have been obtained for both accuracy as well as efficiency.
机译:MRI中的不同对比度的图像可以包含互补信息,可以突出显示不同的组织类型。此类数据集通常需要共同注册任何进一步处理。提出了一种基于恢复这些图像对的联合统计数据的新颖且有效的非刚性登记方法。使用联合统计的解构进行注册,然后通过执行Deconvolve统计数据回到空间域以形成初步登记。通过高斯空间平滑,空间转换也会进行规范化。将注册方法与B样条进行比较,并用模拟的Shepp-logan Phantom验证,具有BrainWeb Phantom,以及实际数据集。已经获得了准确性以及效率的改进的结果。

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