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Deformable Registration for Geometric Distortion Correction of Diffusion Tensor Imaging

机译:扩散张量成像几何畸变校正的可变形配准

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Geometric distortion of diffusion tensor imaging (DTI) always results in inner brain tissues shift and brain contour deformation and it will certainly lead to the uncertainty of DTI and DTI fiber tracking in the planning of neurosurgeries. In this study, we investigated the accuracy of two deformable registration algorithms for distortion correction of DTI in the application of computer assisted neurosurgery system. The first algorithm utilized cubic B-spline modeled constrained deformation field (BSP) registration of the 3D distorted DTI image to 3D anatomical image, while the second algorithm used multi-resolution B-spline deformable registration. Based on the results, we found that multi-resolution B-spline registration is more reliable than BSP registration for distortion correction of multi-sequence DTI images, the contour deformation and inner brain tissue displacement could be well calibrated in 2D and 3D visualizations. The mesh resolution of B-spline transform plays a great role in distortion correction. This multi-resolution B-spline deformable registration can help to improve the geometric fidelity of DTI and allows correcting fiber tract distortions which is critical for the application of DTI in computer assisted neurosurgery system.
机译:弥散张量成像(DTI)的几何畸变总是导致大脑内部组织移位和大脑轮廓变形,并且肯定会导致神经外科手术计划中DTI和DTI纤维追踪的不确定性。在这项研究中,我们调查了两种可变形配准算法在计算机辅助神经外科系统应用中纠正DTI失真的准确性。第一种算法使用三次B样条建模的3D扭曲DTI图像到3D解剖图像的约束变形场(BSP)配准,而第二种算法则使用多分辨率B样条可变形配准。根据结果​​,我们发现多分辨率B样条配准比BSP配准在多序列DTI图像的畸变校正方面更可靠,在2D和3D可视化中可以很好地校正轮廓变形和大脑内组织位移。 B样条变换的网格分辨率在失真校正中起着重要作用。这种多分辨率B样条可变形配准可以帮助改善DTI的几何保真度,并可以校正纤维束变形,这对于DTI在计算机辅助神经外科系统中的应用至关重要。

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