Disentangling micro from mesostructure by diffusion MRI: A Bayesian approach

Disentangling micro from mesostructure by diffusion MRI: A Bayesian approach

Diffusion-sensitized magnetic resonance imaging probes the cellular structure of the human brain, but the primary microstructural information gets lost in averaging over higher-level, mesoscopic tissue organization such as different orientations of neuronal fibers. While such averaging is inevitable due to the limited imaging resolution, we propose a method for disentangling the microscopic cel...

A Bayesian approach for image denoising in MRI

Magnetic Resonance Imaging (MRI) is a notable medical imaging technique that is based on Nuclear Magnetic Resonance (NMR). MRI is a safe imaging method with high contrast between soft tissues, which made it the most popular imaging technique in clinical applications. MR Imagechr('39')s visual quality plays a vital role in medical diagnostics that can be severely corrupted by existing noise duri...

Bayesian Approach to Disentangling Technical and Environmental Productivity

This paper models the firm’s production process as a system of simultaneous technologies for desirable and undesirable outputs. Desirable outputs are produced by transforming inputs via the conventional transformation function, whereas (consistent with the material balance condition) undesirable outputs are by-produced via the so-called “residual generation technology”. By separating the produc...

From Micro to Macro: A Study of Human Brain Structure Based on Diffusion MRI and Neuronal Networks BY JOHNSON

Disentangling sources of anomalous diffusion.

We show that some important properties of subdiffusion of unknown origin (including ones of mixed origins) can be easily assessed when finding the "fundamental moment" of the corresponding random process, i.e., the one which is additive in time. In subordinated processes, the index of the fundamental moment is inherited from the parent process and its time dependence from the leading one. In mo...