Acceleration of Range Points Migration-Based Microwave Imaging for Nondestructive Testing

We report on an experimental investigation of the properties of volume holographic recording in photopolymerizable nanoparticle?polymer composites (NPCs) doped with chain transferring multifunctional di- and tri-thiols as chain transfer agents. It is shown that the incorporation of the multifunctional thiols into NPCs more strongly influences on volume holographic recording than that doped with mono-thiol since more chemical reactions involve in the polymer network formation. It is found that, as similar to the case of mono-thiol doping, there exist optimum concentrations of di- and tri-thiols for maximizing the saturated refractive index modulation. It is also seen that recording sensitivity monotonically decreases with an increase in multifunctional thiol concentration due to the partial inhibition of the photopolymerization event by excessive thiols

A Deep Cascade of Convolutional Neural Networks for MR Image Reconstruction

The acquisition of Magnetic Resonance Imaging (MRI) is inherently slow. Inspired by recent advances in deep learning, we propose a framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that for Cartesian undersampling of 2D cardiac MR images, the proposed method outperforms the state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, in terms of reconstruction error, perceptual quality and reconstruction speed for both 3-fold and 6-fold undersampling. Compared to DLMRI, the error produced by the method proposed is approximately twice as small, allowing to preserve anatomical structures more faithfully. Using our method, each image can be reconstructed in 23 ms, which is fast enough to enable real-time applications

Interim Design Report

The International Design Study for the Neutrino Factory (the IDS-NF) was established by the community at the ninth "International Workshop on Neutrino Factories, super-beams, and beta- beams" which was held in Okayama in August 2007. The IDS-NF mandate is to deliver the Reference Design Report (RDR) for the facility on the timescale of 2012/13. In addition, the mandate for the study [3] requires an Interim Design Report to be delivered midway through the project as a step on the way to the RDR. This document, the IDR, has two functions: it marks the point in the IDS-NF at which the emphasis turns to the engineering studies required to deliver the RDR and it documents baseline concepts for the accelerator complex, the neutrino detectors, and the instrumentation systems. The IDS-NF is, in essence, a site-independent study. Example sites, CERN, FNAL, and RAL, have been identified to allow site-specific issues to be addressed in the cost analysis that will be presented in the RDR. The choice of example sites should not be interpreted as implying a preferred choice of site for the facility

Exploiting flow dynamics for super-resolution in contrast-enhanced ultrasound

Ultrasound localization microscopy offers new radiation-free diagnostic tools for vascular imaging deep within the tissue. Sequential localization of echoes returned from inert microbubbles with low-concentration within the bloodstream reveal the vasculature with capillary resolution. Despite its high spatial resolution, low microbubble concentrations dictate the acquisition of tens of thousands of images, over the course of several seconds to tens of seconds, to produce a single super-resolved image. %since each echo is required to be well separated from adjacent microbubbles. Such long acquisition times and stringent constraints on microbubble concentration are undesirable in many clinical scenarios. To address these restrictions, sparsity-based approaches have recently been developed. These methods reduce the total acquisition time dramatically, while maintaining good spatial resolution in settings with considerable microbubble overlap. %Yet, non of the reported methods exploit the fact that microbubbles actually flow within the bloodstream. % to improve recovery. Here, we further improve sparsity-based super-resolution ultrasound imaging by exploiting the inherent flow of microbubbles and utilize their motion kinematics. While doing so, we also provide quantitative measurements of microbubble velocities. Our method relies on simultaneous tracking and super-localization of individual microbubbles in a frame-by-frame manner, and as such, may be suitable for real-time implementation. We demonstrate the effectiveness of the proposed approach on both simulations and {\it in-vivo} contrast enhanced human prostate scans, acquired with a clinically approved scanner.Comment: 11 pages, 9 figure