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Non-rigid image registration for enhanced localization in magnetic resonance brain imaging.

机译：非刚性图像配准可增强磁共振脑成像中的定位。

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Technical advances in magnetic resonance imaging (MRI) have lead to clinical and scientific applications with higher spatial and temporal resolution. One area of interest is in neuroscience and neuropathology studies towards revealing the ambiguities of human brain function and mental brain disorders. As more challenging patient populations are imaged and more advanced experiments are designed, there is an increasing demand for more accurate localization of brain function and structure. Localization of functional information and fusion of magnetic resonance images has been addressed through image registration techniques. Accurate rigid and affine registration techniques are now part of the standard brain image processing toolkits, which aim at correcting the effect of head motion and repositioning into a sub-voxel range. However, local spatial distortions may cause typical localization errors of up to 10 millimeters in magnetic resonance images acquired by Echo-Planar Imaging (EPI). This compromises the accuracy of localization and registration in functional MRI, Diffusion Tensor Imaging and Arterial Spin Labeling. Such spatial distortions are mainly caused by field inhomogeneity and susceptibility artifacts and cannot be compensated by rigid and affine registration techniques. Therefore, the main thrust of this dissertation has been the deployment of non-rigid registration for the correction of local spatial distortions in EPI. As a main challenge, quantitative in-vivo validation criteria have been devised to support the routine use of the developed techniques as part of a toolkit named NPTK, or Neuroimage Processing ToolKit. The outcome of this research makes up the core component of NPTK for enhanced localization. The technical developments on the optimization aspects of information similarity measures carried out as part of this research is generally applicable to high-dimensional optimization problems including non-rigid registration, information theoretic learning, pattern classification, and bioinformatics.
机译：磁共振成像（MRI）的技术进步已导致具有更高时空分辨率的临床和科学应用。感兴趣的领域之一是神经科学和神经病理学研究，旨在揭示人脑功能和精神性脑疾病的歧义。随着对更具挑战性的患者群体成像并设计了更高级的实验，对脑功能和结构的更精确定位的需求日益增长。功能信息的定位和磁共振图像的融合已通过图像配准技术解决。现在，准确的刚性和仿射配准技术已成为标准脑部图像处理工具包的一部分，该工具包旨在纠正头部运动的影响并将其重新定位到亚体素范围。但是，局部空间畸变可能会在通过回波平面成像（EPI）采集的磁共振图像中引起高达10毫米的典型定位误差。这会损害功能性MRI，扩散张量成像和动脉自旋标记的定位和配准的准确性。这种空间畸变主要是由场的不均匀性和磁化伪影引起的，不能通过刚性和仿射配准技术来补偿。因此，本论文的主要推力是采用非刚性配准来校正EPI中的局部空间畸变。作为一项主要挑战，定量体内验证标准已被设计为支持开发技术的常规使用，并将其作为名为NPTK或Neuroimage Processing ToolKit的工具包的一部分。这项研究的结果构成了NPTK增强本地化的核心组成部分。作为本研究的一部分，在信息相似性度量的优化方面进行的技术开发通常适用于高维优化问题，包括非刚性注册，信息理论学习，模式分类和生物信息学。

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