Deep Learning for Accelerated Ultrasound Imaging

In portable, 3-D, or ultra-fast ultrasound (US) imaging systems, there is an increasing demand to reconstruct high quality images from limited number of data. However, the existing solutions require either hardware changes or computationally expansive algorithms. To overcome these limitations, here we propose a novel deep learning approach that interpolates the missing RF data by utilizing the sparsity of the RF data in the Fourier domain. Extensive experimental results from sub-sampled RF data from a real US system confirmed that the proposed method can effectively reduce the data rate without sacrificing the image quality.Comment: Invited paper for ICASSP 2018 Special Session for "Machine Learning in Medical Imaging: from Measurement to Diagnosis

A Fast Splitting Method for efficient Split Bregman Iterations

In this paper we propose a new fast splitting algorithm to solve the Weighted Split Bregman minimization problem in the backward step of an accelerated Forward-Backward algorithm. Beside proving the convergence of the method, numerical tests, carried out on different imaging applications, prove the accuracy and computational efficiency of the proposed algorithm

Laser-wakefield accelerators as hard x-ray sources for 3D medical imaging of human bone

A bright μm-sized source of hard synchrotron x-rays (critical energy Ecrit > 30 keV) based on the betatron oscillations of laser wakefield accelerated electrons has been developed. The potential of this source for medical imaging was demonstrated by performing micro-computed tomography of a human femoral trabecular bone sample, allowing full 3D reconstruction to a resolution below 50 μm. The use of a 1 cm long wakefield accelerator means that the length of the beamline (excluding the laser) is dominated by the x-ray imaging distances rather than the electron acceleration distances. The source possesses high peak brightness, which allows each image to be recorded with a single exposure and reduces the time required for a full tomographic scan. These properties make this an interesting laboratory source for many tomographic imaging applications

Scanning ultrafast electron microscopy

Progress has been made in the development of four-dimensional ultrafast electron microscopy, which enables space-time imaging of structural dynamics in the condensed phase. In ultrafast electron microscopy, the electrons are accelerated, typically to 200 keV, and the microscope operates in the transmission mode. Here, we report the development of scanning ultrafast electron microscopy using a field-emission-source configuration. Scanning of pulses is made in the single-electron mode, for which the pulse contains at most one or a few electrons, thus achieving imaging without the space-charge effect between electrons, and still in ten(s) of seconds. For imaging, the secondary electrons from surface structures are detected, as demonstrated here for material surfaces and biological specimens. By recording backscattered electrons, diffraction patterns from single crystals were also obtained. Scanning pulsed-electron microscopy with the acquired spatiotemporal resolutions, and its efficient heat-dissipation feature, is now poised to provide in situ 4D imaging and with environmental capability

Interplay of Boltzmann equation and continuity equation for accelerated electrons in solar flares

During solar flares a large amount of electrons are accelerated within the plasma present in the solar atmosphere. Accurate measurements of the motion of these electrons start becoming available from the analysis of hard X-ray imaging-spectroscopy observations. In this paper, we discuss the linearized perturbations of the Boltzmann kinetic equation describing an ensemble of electrons accelerated by the energy release occurring during solar flares. Either in the limit of high energy or at vanishing background temperature such an equation reduces to a continuity equation equipped with an extra force of stochastic nature. This stochastic force is actually described by the well known energy loss rate due to Coulomb collision with ambient particles, but, in order to match the collision kernel in the linearized Boltzmann equation it needs to be treated in a very specific manner. In the second part of the paper the derived continuity equation is solved with some hyperbolic techniques, and the obtained solution is written in a form suitable to be compared with data gathered by hard X-ray imaging-spectroscopy telescopes. Finally, a first validation of the model with NASA Reuven Ramaty High Energy Solar Spectroscopic Imager spectrometer measurements is provided.Comment: submitted to SIAM/ASA Journal on Uncertainty Quantificatio

Accelerated Cardiac Diffusion Tensor Imaging Using Joint Low-Rank and Sparsity Constraints

Objective: The purpose of this manuscript is to accelerate cardiac diffusion tensor imaging (CDTI) by integrating low-rankness and compressed sensing. Methods: Diffusion-weighted images exhibit both transform sparsity and low-rankness. These properties can jointly be exploited to accelerate CDTI, especially when a phase map is applied to correct for the phase inconsistency across diffusion directions, thereby enhancing low-rankness. The proposed method is evaluated both ex vivo and in vivo, and is compared to methods using either a low-rank or sparsity constraint alone. Results: Compared to using a low-rank or sparsity constraint alone, the proposed method preserves more accurate helix angle features, the transmural continuum across the myocardium wall, and mean diffusivity at higher acceleration, while yielding significantly lower bias and higher intraclass correlation coefficient. Conclusion: Low-rankness and compressed sensing together facilitate acceleration for both ex vivo and in vivo CDTI, improving reconstruction accuracy compared to employing either constraint alone. Significance: Compared to previous methods for accelerating CDTI, the proposed method has the potential to reach higher acceleration while preserving myofiber architecture features which may allow more spatial coverage, higher spatial resolution and shorter temporal footprint in the future.Comment: 11 pages, 16 figures, published on IEEE Transactions on Biomedical Engineerin