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VALIDATION OF A NEW OPTIMISATION ALGORITHM FOR REGISTRATION TASKS IN MEDICAL IMAGING

机译:验证医学成像中注册任务的新优化算法

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A number of problems frequently encountered in brain image analysis can be conveniently solved within a registration framework, such as alignment of mono- or multi-sequence Magnetic Resonance Images (MRI) for single or multiple subjects, computation of the cerebral mid-sagittal plane in anatomical or diffusion-tensor MRI, correction of acquisition distortions in diffusion-weighted MRI, etc. A widely used approach for registration tasks consists of maximising a similarity criterion between the intensities of the images to be matched. In this context, efficient optimisation methods are needed to obtain good performances. In this paper, we introduce a new optimisation algorithm (called NEWUOA) to address the above registration problems, and we demonstrate its robustness and accuracy properties.
机译:脑图像分析中经常遇到的许多问题可以在登记框架内方便地解决,例如单个或多个受试者的单序或多序列磁共振图像(MRI)的对准,计算脑中矢状平面的计算解剖学或扩散 - 张量MRI,扩散加权MRI中的采集畸变等校正。广泛使用的登记任务方法包括最大化要匹配的图像的强度之间的相似性标准。在这种情况下,需要有效的优化方法来获得良好的性能。在本文中,我们介绍了一种新的优化算法(称为Newuoa)来解决上述注册问题,并且我们展示了其稳健性和准确性。

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