Bhushan Chitresh, Haldar Justin P, Joshi Anand A, Leahy Richard M
Signal and Image Processing Institute, University of Southern California, Los Angeles, CA, USA.
Signal Inf Process Assoc Annu Summit Conf APSIPA Asia Pac. 2012 Dec;2012.
Echo Planar Imaging (EPI) is the standard pulse sequence used in fast diffusion-weighted magnetic resonance imaging (MRI), but is sensitive to susceptibility-induced inhomogeneities in the main B magnetic field. In diffusion MRI of the human head, this leads to geometric distortion of the brain in reconstructed diffusion images, and a lack of correspondence with undistorted high-resolution MRI scans that are used to define the subject anatomy. In this study, we have tested an approach to estimate and correct this distortion of using a non-linear registration framework based on mutual-information. We use the commonly acquired anatomical image as the registration-template and constrain the registration using spatial regularization and physics-based information about the characteristics of the distortion, but without requiring any additional data collection. Results are shown for simulated and experimental data.
回波平面成像（EPI）是快速扩散加权磁共振成像（MRI）中使用的标准脉冲序列，但对主B磁场中由磁化率引起的不均匀性敏感。在人体头部的扩散MRI中，这会导致重建的扩散图像中大脑出现几何变形，并且与用于定义受试者解剖结构的未变形高分辨率MRI扫描缺乏对应关系。在本研究中，我们测试了一种基于互信息的非线性配准框架来估计和校正这种变形的方法。我们使用通常采集的解剖图像作为配准模板，并使用空间正则化和关于变形特征的基于物理的信息来约束配准，而无需任何额外的数据采集。给出了模拟数据和实验数据的结果。
