Richard M. Leahy

TL;DR: In this paper, a Bayesian PET reconstruction method that incorporates anatomical information extracted from a partial volume segmentation of a co-registered magnetic resonance (MR) image is described. But the method does not consider the anatomical information to guide the formation of a binary process representing region boundaries, rather than use the segmented anatomical image as a template to customize the Gibbs energy in such a way that they apply thin-plate smoothing within homogeneous tissue regions while enforcing zeroth corder continuity as we transition from homogeneous to partial volume regions.

TL;DR: The new hybrid-BCI-DNI atlas is a high-resolution MPRAGE, single-subject atlas, constructed using both anatomical and functional information to guide the parcellation of the cerebral cortex to provide a quantitative measure of reliability of each subdivision to users of the atlas.

TL;DR: It is argued that partial-correlation is a better measure for extracting connectivity matrix from multivariate data because it removes the effects of confounding correlations that get introduced due to canonical dependence between data.

TL;DR: This hybrid approach to iterative PET image reconstruction is compared to each of the component algorithms in application to simulated PET data demonstrating a reduction of at least 50% in iterations required for effective convergence compared to use of PCG alone.

TL;DR: A longitudinal sample of 900 twins in two assessments in late childhood and mid-adolescence was investigated to verify whether relationships exist between FAP and both aggressive and nonaggressive ASB.