Automatic detection of gadolinium-enhancing multiple sclerosis lesions in brain MRI using conditional random fields.

Gadolinium-enhancing lesions in brain magnetic resonance imaging of multiple sclerosis (MS) patients are of great interest since they are markers of disease activity. Identification of gadolinium-enhancing lesions is particularly challenging because the vast majority of enhancing voxels are associated with normal structures, particularly blood vessels. Furthermore, these lesions are typically small and in close proximity to vessels.

TRAF6 and IRF7 control HIV replication in macrophages.

The innate immune system recognizes virus infection and evokes antiviral responses which include producing type I interferons (IFNs). The induction of IFN provides a crucial mechanism of antiviral defense by upregulating interferon-stimulated genes (ISGs) that restrict viral replication. ISGs inhibit the replication of many viruses by acting at different steps of their viral cycle.

Evaluating intensity normalization on MRIs of human brain with multiple sclerosis.

Intensity normalization is an important pre-processing step in the study and analysis of Magnetic Resonance Images (MRI) of human brains. As most parametric supervised automatic image segmentation and classification methods base their assumptions regarding the intensity distributions on a standardized intensity range, intensity normalization takes on a very significant role. One of the fast and accurate approaches proposed for intensity normalization is that of Nyul and colleagues.

A general framework for analyzing data from two short time-series microarray experiments.

We propose a general theoretical framework for analyzing differentially expressed genes and behavior patterns from two homogenous short time-course data. The framework generalizes the recently proposed Hilbert-Schmidt Independence Criterion (HSIC)-based framework adapting it to the time-series scenario by utilizing tensor analysis for data transformation. The proposed framework is effective in yielding criteria that can identify both the differentially expressed genes and time-course patterns of interest between two time-series experiments without requiring to explicitly cluster the data.

Detection of Gad-enhancing lesions in multiple sclerosis using conditional random fields.

Identification of Gad-enhancing lesions is of great interest in Multiple Sclerosis (MS) disease since they are associated with disease activity. Current techniques for detecting Gad-enhancing lesions use a contrast agent (Gadolinium) which is administered intravenously to highlight Gad-enhancing lesions. However, the contrast agent not only highlights these lesions, but also causes other tissues (e.