This paper presents a hierarchical Bayesian model to reconstruct sparse images when the observations are obtained from linear transformations and corrupted by an additive white Gau...
Nicolas Dobigeon, Alfred O. Hero, Jean-Yves Tourne...
In this paper, we propose an "in-network" diversity combining scheme for image transport over wireless sensor networks. We consider a wireless sensor network with both w...
Abstract. We apply sparse Bayesian learning methods, automatic relevance determination (ARD) and predictive ARD (PARD), to Alzheimer’s disease (AD) classification to make accura...
Li Shen, Yuan Qi, Sungeun Kim, Kwangsik Nho, Jing ...
Quantitative measurements of changes in evolving brain pathology, such as multiple sclerosis lesions and brain tumors, are important for clinicians to perform pertinent diagnoses a...
We investigated nonrigid co-registration of PET and MR breast images to improve diagnostic specificity in difficult-to-interpret mammograms, and ultimately to avoid biopsy. A defo...