Abstract: A method for simulating a nanowire network structure and dynamics is presented. The method includes selecting a number of nanowires representing the nanowire network structure, where each nanowire is simulated with a mean length randomly drawn from a gamma distribution and an orientation selected from a uniform distribution. The method further includes identifying intersection points between overlapping nanowires within the nanowire network structure and representing the nanowire network structure with a graph representation in which the nanowires are represented as nodes and the intersection points are represented as edges. Further, simulating a source electrode on a first location of the nanowire network structure for simulating an applied input voltage, applying to the source electrode a time-varying input voltage having a fixed duration, and solving Kirchoff s current law equations for the time-varying input voltage to obtain a time-dependent voltage function across the nanowire network structure.

Abstract: Systems and methods are provided for susceptibility contrast imaging of nanoparticles at low magnetic fields. A susceptibility-based MRI technique, such as imaging with a balanced steady-state free precession (bSSFP) pulse sequence, may be used for imaging a contrast agent such as biocompatible superparamagnetic nanoparticles at ultra-low fields. The contrast agent and imaging technique may be used to improving the visibility of anatomical structures and detecting diseases, such as cancer, with low-field MRI.

Abstract: Systems and methods are provided for susceptibility contrast imaging of nanoparticles at low magnetic fields. A susceptibility-based MRI technique, such as imaging with a balanced steady-state free precession (bSSFP) pulse sequence, may be used for imaging a contrast agent such as biocompatible superparamagnetic nanoparticles at ultra-low fields. The contrast agent and imaging technique may be used to improving the visibility of anatomical structures and detecting diseases, such as cancer, with low-field MRI.

Abstract: A method of adaptive suppression of over-smoothing in noise/artefact reduction techniques such as total variation minimization or other compressed sensing strategies for Cone Beam Computed Tomography (CBCT) images, the method including the steps of: (a) inputting a CBCT image; (b) identifying the anatomical structures of interest in the CBCT images by exploiting their likely shapes, attenuation coefficients, sizes, positions, or any other similar features that can be used to identify them from an image; (c) extracting intensity, gradient, or other image-related information of the identified anatomical structures from the CBCT image; (d) adaptively suppressing over-smoothing in noise/artefact reduction techniques such as total-variation minimization or other compressed sensing strategies at the anatomical structures of interest using the information of the anatomical structures extracted previously.