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      Improved optimization for the robust and accurate linear registration and motion correction of brain images.

      1 , , ,
      NeuroImage
      Elsevier BV

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          Abstract

          Linear registration and motion correction are important components of structural and functional brain image analysis. Most modern methods optimize some intensity-based cost function to determine the best registration. To date, little attention has been focused on the optimization method itself, even though the success of most registration methods hinges on the quality of this optimization. This paper examines the optimization process in detail and demonstrates that the commonly used multiresolution local optimization methods can, and do, get trapped in local minima. To address this problem, two approaches are taken: (1) to apodize the cost function and (2) to employ a novel hybrid global-local optimization method. This new optimization method is specifically designed for registering whole brain images. It substantially reduces the likelihood of producing misregistrations due to being trapped by local minima. The increased robustness of the method, compared to other commonly used methods, is demonstrated by a consistency test. In addition, the accuracy of the registration is demonstrated by a series of experiments with motion correction. These motion correction experiments also investigate how the results are affected by different cost functions and interpolation methods.

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          Spatial registration and normalization of images

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            Automatic 3D Intersubject Registration of MR Volumetric Data in Standardized Talairach Space

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              MRI-PET Registration with Automated Algorithm

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                Author and article information

                Journal
                Neuroimage
                NeuroImage
                Elsevier BV
                1053-8119
                1053-8119
                Oct 2002
                : 17
                : 2
                Affiliations
                [1 ] Oxford Centre for Functional Magnetic Resonance Imaging of the Brain, John Radcliffe Hospital, Headington, United Kingdom.
                Article
                S1053811902911328
                10.1016/s1053-8119(02)91132-8
                12377157
                db7a3f8e-33c6-45b8-b00b-98196e31a9e8
                History

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