Multimodal Image Coregistration and Partitioning—A Unified Framework

TL;DR: The probabilistic subdivision of the corpus callosum by connecting cortical gray matter provides a more precise understanding of the CC.

TL;DR: The findings suggest that signal changes occur in patients with Alzheimer's disease in the substantia innominata which may be related to the loss or degeneration of cholinergic neurones and correspond to regional cortical grey matter atrophy.

TL;DR: Robust activation of a semantic network extending from left inferior frontal cortex into the inferior temporal lobe is found, but no differences as a function of word class are found.

TL;DR: The results suggest that in the cortical areas showing a strong correlation of deformation with age, caution should be used in assigning imaging results in children to a specific morphological structure, and to minimize the amount ofDeformation during non‐linear spatial normalization, a pediatric template should be use.

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.