This paper addresses the problem of creating probabilistic brain atlases from manually
labeled training data. Probabilistic atlases are typically constructed by counting the relative …

This paper addresses the problem of creating probabilistic brain atlases from manually
labeled training data. We propose a general mesh-based atlas representation, and compare …

The segmentation of the subcortical structures of the brain is required for many forms of
quantitative neuroanatomic analysis. The volumetric and shape parameters of structures …

We propose a novel framework for the automatic propagation of a set of manually labeled
brain atlases to a diverse set of images of a population of subjects. A manifold is learned …

Spatial priors, such as probabilistic atlases, play an important role in MRI segmentation.
However, the availability of comprehensive, reliable and suitable manual segmentations for …

We describe the construction of a digital brain atlas composed of data from manually
delineated MRI data. A total of 56 structures were labeled in MRI of 40 healthy, normal …

In non-rigid registration, the tradeoff between warp regularization and image fidelity is
typically determined empirically. In atlas-based segmentation, this leads to a probabilistic …

The logarithm of the odds ratio (LogOdds) is frequently used in areas such as artificial neural
networks, economics, and biology, as an alternative representation of probabilities. Here, we …

We present a robust and accurate atlas-based brain segmentation method which uses
multiple initial structure segmentations to simultaneously drive the image registration and …

This paper examines the multiple atlas random diffeomorphic orbit model in Computational
Anatomy (CA) for parameter estimation and segmentation of subcortical and ventricular …