Multimodal Image Coregistration and Partitioning—A Unified Framework

TL;DR: Results suggest that disturbance in exploratory eye movement in schizophrenia spectrum patients may be related to neural network dysfunction in FEF, SEF and PEF, which are the eye movement related areas, and in the inferior frontal region that may berelated to information organization.

TL;DR: In this paper, an alignment method and apparatus for aligning images having different imaged regions with improved alignment accuracy is presented, where two images having an overlapping area are aligned with each other based on the amount of shift when one of the two images is aligned with the overall reference image.

TL;DR: A positive correlation between longitudinal changes in Cho and in lesion volume in moderately hypointense lesions implied that lesion size is mediated by chronic inflammation, and other results are integrated in a discussion on the steady‐state metabolism of lesion evolution in multiple sclerosis, viewed in the context of conventional MRI measures.

TL;DR: How action-perception coupling may enable spontaneous near transfer and action simulation during action observation is discussed and shows that after associative learning, a series of sensory events can trigger sequence-specific representations in both sensory and motor networks.

TL;DR: A general technique that facilitates nonlinear spatial (stereotactic) normalization and image realignment is presented that minimizes the sum of squares between two images following non linear spatial deformations and transformations of the voxel (intensity) values.

TL;DR: A computer algorithm for the three-dimensional alignment of PET images is described that relies on anatomic information in the images rather than on external fiducial markers and can be applied retrospectively, during acquisition, to reposition the scanner gantry and bed to match an earlier study.

TL;DR: The authors have collected over 300 MRI volumetric datasets from normal individuals and transformed these datasets into stereotaxic space using a 3D linear re-sampling algorithm, and generated a series of statistical measures which express this population nonlinear variability in the form of parametric volumes.

TL;DR: The results indicate that retrospective techniques have the potential to produce satisfactory results much of the time, but that visual inspection is necessary to guard against large errors.