Evaluation of imaging protocol for ECT based on CS image reconstruction algorithm

Single-photon emission computerized tomography and positron emission tomography are essential medical imaging tools, for which the sampling angle number and scan time should be carefully chosen to give a good compromise between image quality and radiopharmaceutical dose. In this study, the image quality of different acquisition protocols was evaluated via varied angle number and count number per angle with Monte Carlo simulation data. It was shown that, when similar imaging counts were used, the factor of acquisition counts was more important than that of the sampling number in emission computerized tomography. To further reduce the activity requirement and the scan duration, an iterative image reconstruction algorithm for limited-view and low-dose tomography based on compressed sensing theory has been developed. The total variation regulation was added to the reconstruction process to improve the signal to noise Ratio and reduce artifacts caused by the limited angle sampling. Maximization of the maximum likelihood of the estimated image and the measured data and minimization of the total variation of the image are alternatively implemented. By using this advanced algorithm, the reconstruction process is able to achieve image quality matching or exceed that of normal scans with only half of the injection radiopharmaceutical dose.     

A Compton scattering image reconstruction algorithm based on total variation minimization

Compton scattering imaging is a novel radiation imaging method using scattered photons.Its main characteristics are detectors that do not have to be on the opposite side of the source,so avoiding the rotation process.The reconstruction problem of Compton scattering imaging is the inverse problem to solve electron densities from nonlinear equations,which is ill-posed.This means the solution exhibits instability and sensitivity to noise or erroneous measurements.Using the theory for reconstruction of sparse images,a reconstruction algorithm based on total variation minimization is proposed.The reconstruction problem is described as an optimization problem with nonlinear data-consistency constraint.The simulated results show that the proposed algorithm could reduce reconstruction error and improve image quality,especially when there are not enough measurements.     

A Combined Reconstruction Algorithm for Limited-View Multi-Element Photoacoustic Imaging

We present a photoacoustic imaging system with a linear transducer array scanning in limited-view felds and develop a combined reconstruction algorithm, which is a combination of the limited-field filtered back projection （LFBP） algorithm and the simultaneous iterative reconstruction technique （SIRT） algorithm, to reconstruct the optical absorption distribution. In this algorithm, the LFBP algorithm is exploited to reconstruct the original photoacoustic image, and then the SIRT algorithm is used to improve the quality of the final reconstructed photoacoustic image. Numerical simulations with calculated incomplete data validate the reliability of this algorithm and the reconstructed experimental results further demonstrate that the combined reconstruction algorithm effectively reduces the artifacts and blurs and yields better quality of reconstruction image than that with the LFBP algorithm.     

Compressive sampling photoacoustic tomography based on edge expander codes and TV regularization

A new photoacoustic （PA） signal sampling and image reconstruction method, called compressive sampling PA tomography （CSPAT）, is recently proposed to make low sampling rate and high-resolution PA tomogra- phy possible. A key problem within the CSPAT framework is the design of optic masks. We propose to use edge expander codes-based masks instead of the conventional random distribution masks, and efficient total variation （TV） regularization-based model to formulate the associated problem. The edge expander codesbased masks, corresponding to non-uniform sampling schemes, are validated by both theoretical analysis and results from computer simulations. The proposed method is expected to enhance the capability of CSPAT for reducing the number of measurements and fast data acquisition.     

An advanced fully 3D OSEM reconstruction for positron emission tomography

A fully 3D OSEM reconstruction method for positron emission tomography （PET） based on symmetries and sparse matrix technique is described. Great savings in both storage space and computation time were achieved by exploiting the symmetries of scanner and sparseness of the system matrix. More reduction of storage requirement was obtained by introducing the approximation of system matrix. Iteration-filter was performed to restrict image noise in reconstruction. Performances of simulation data and phantom data got from Micro-PET （Type： Epuls-166） demonstrated that similar image quality was achieved using the approximation of the system matrix.     

Holographic display based on compressive sensing (Invited Paper)

We propose a method to improve the quality of the reconstructed images based on compressive sensing principles. The pseudo-inverse matrix and the total variation minimization algorithms are combined to reduce the sampling number of the computer generated hologram. Numerical simulations are performed and the results indicate that the peak signal to noise ratio is increased and the sampling ratio is decreased at the same time for holographic display.     

Deep learning for image reconstruction in thermoacoustic tomography

Microwave-induced thermoacoustic tomography(TAT)is a rapidly-developing noninvasive imaging technique that integrates the advantages of microwave imaging and ultrasound imaging.While an image reconstruction algorithm is critical for the TAT,current reconstruction methods often creates significant artifacts and are computationally costly.In this work,we propose a deep learning-based end-to-end image reconstruction method to achieve the direct reconstruction from the sinogram data to the initial pressure density image.We design a new network architecture TAT-Net to transfer the sinogram domain to the image domain with high accuracy.For the scenarios where realistic training data are scarce or unavailable,we use the finite element method(FEM)to generate synthetic data where the domain gap between the synthetic and realistic data is resolved through the signal processing method.The TAT-Net trained with synthetic data is evaluated through both simulations and phantom experiments and achieves competitive performance in artifact removal and robustness.Compared with other state-of-the-art reconstruction methods,the TAT-Net method can reduce the root mean square error to 0.0143,and increase the structure similarity and peak signal-to-noise ratio to 0.988 and 38.64,respectively.The results obtained indicate that the TAT-Net has great potential applications in improving image reconstruction quality and fast quantitative reconstruction.     

High total variation-based method for sparse-view photoacoustic reconstruction

We propose a novel method by combining the total variation（TV） with the high-degree TV（HDTV） to improve the reconstruction quality of sparse-view sampling photoacoustic imaging（PAI）. A weighing function is adaptively updated in an iterative way to combine the solutions of the TV and HDTV minimizations. The fast iterative shrinkage/thresholding algorithm is implemented to solve both the TV and the HDTV minimizations with better convergence rate. Numerical results demonstrate the superiority and efficiency of the proposed method on sparse-view PAI. In vitro experiments also illustrate that the method can be used in practical sparse-view PAI.     

An ART iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging

X-ray diffraction enhanced imaging （DEI） has extremely high sensitivity for weakly absorbing low- Z samples in medical and biological fields. In this paper, we propose an Algebra Reconstruction Technique （ART） iterative reconstruction algorithm for computed tomography of diffraction enhanced imaging （DEI-CT）. An Ordered Subsets （OS） technique is used to accelerate the ART reconstruction. Few-view reconstruction is also studied, and a partial differential equation （PDE） type filter which has the ability of edge-preserving and denoising is used to improve the image quality and eliminate the artifacts. The proposed algorithm is validated with both the numerical simulations and the experiment at the Beijing synchrotron radiation facility （BSRF）.     

Sub-pixel processing algorithm of the reducing boundary recursive error in staring FPA micro-scanning imaging

<正>By analyzing the error distribution rule of the boundary recursive reconstruction algorithm in controlled micro-scanning,a sub-pixel image processing algorithm is proposed to reduce the error.The gray statistical principle is used in the algorithm to optimize the error and acquire the sub-pixel image that approximates the original image.The simulation result shows that the effect of this algorithm is better than the oversample and simple boundary recursive algorithm(BRA),and it results in a good effect both in those of visible light and infrared imaging systems.Therefore,the application of this algorithm will enhance the performance of optoelectronic imaging systems.     

△-Resonances in Ground State Properties of ^40 20Ca Spherical Cold Finite Nucleus at Equilibrium and under Compression

The ground state properties of the spherical nucleus ^40Ca have been investigated by using constrained spherical Hartree Fock （CSHF） approximation at equilibrium and under high radial compression in a six major shells. The effective baryon-baryon interaction that includes the △（1236） resonance freedom degrees to calculate nuclear properties is used. The nucleon-nucleon （N-N） interaction is based on Reid soft core （RSC） potential. The results of calculations show that much of increase in the nuclear energy generated under compression is used to create the massive △ particles. The number of △ ＇s can be increased to about 2.1% of constituents of nucleus when nuclear density reaches about 1.34 times of normal density. The single particle energy levels are calculated and their behavior under compression is also examined. △ good agreement has been found between current calculations and phenomenological shell model for low lying single-particle spectra. The gap between shells is very clear and L-S coupling become stronger as increasing the static load on the nucleus. The results show a considerable reduction in compressibility when freedom degrees of △＇s are taken into account. It has been found that the total nuclear radial density becomes denser in the interior and less dense in the exterior region of nucleus. The surface of nucleus becomes more and more responsive to compression than outer region.     

Experimental research on performances of the imaging plates applied in gamma-ray imaging

Experimental studies on the basic characteristics of IPs applied in T-ray imaging are carried out by utilizing isotopic y-ray sources. The 1.25 MeV T-ray sensitivity of the BAS-MS and BAS-TR imaging plates and their enhanced sensitivity by covering appropriate Compton conversion foils are measured based on the studies of the image intensity linear calibration, time attenuation laws and the influence of scanning parameter settings. The energy-dependent T-ray sensitivity of the IPs is also obtained by the studies of the measured sensitivity and the Monte Carlo simulated energy deposition in the IPs＇ sensitive layer. Furthermore, a method of a sandwich detection structure as well as its primary experimental validations are presented in order to increase the gamma-to-neutron ratio in a y/n mixed radiation field.     

An improved deconvolution method for X-ray coded imaging in inertial confinement fusion

In inertial confinement fusion （ICF）, X-ray coded imaging is considered as the most potential means to diagnose the compressed core. The traditional Richardson-Lucy （RL） method has a strong ability to deblur the image where the noise follows the Poisson distribution. However, it always suffers from over-fitting and noise amplification, especially when the signal-to-noise ratio of image is relatively low. In this paper, we propose an improved deconvolution method for X-ray coded imaging. We model the image data as a set of independent Gaussian distributions and derive the iterative solution with a maximum-likelihood scheme. The experimental results on X-ray coded imaging data demonstrate that this method is superior to the RL method in terms of anti-overfitting and noise suppression.     

DEIReconstructor： a software for diffraction enhanced imaging processing and tomography reconstruction

Diffraction enhanced imaging （DEI） has been widely applied in many fields, especially when imaging low-Z samples or when the difference in the attenuation coefficient between different regions in the sample is too small to be detected. Recent developments of this technique have presented a need for a new software package for data analysis. Here, the Diffraction Enhanced Image Reconstructor （DEIReconstructor）, developed in Matlab, is presented. DEIReconstructor has a user-friendly graphical user interface and runs under any of the 32~bit or 64- bit Microsoft Windows operating systems including XP and WinT. Many of its features are integrated to support imaging preprocessing, extract absorption, refractive and scattering information of diffraction enhanced imaging and allow for parallel-beam tomography reconstruction for DEI-CT. Furthermore, many other useful functions are also implemented in order to simplify the data analysis and the presentation of results. The compiled software package is freely available.     

Medical application of diffraction enhanced imaging in mouse liver blood vessels

Neovascularization is correlative with many processes of diseases, especially for tumor growth, invasion, and metastasis. What is more, these tumor microvessels are totally different from normal vessels in morphology. Therefore, observation of the morphologic distribution of microvessels is one of the key points for many researchers in the field. Using diffraction enhanced imaging （DEI）, we observed the mirocvessles with diameter of about 40 μm in mouse liver. Moreover, the refraction image obtained from DEI shows higher image contrast and exhibits potential use for medical applications.     

High efficiency event-counting thermal neutron imaging using a Gd-doped micro-channel plate

An event-counting thermal neutron imaging detector based on 3 mol % nattGd2O3-doped micro-channel plate （MCP） has been developed and tested. A thermal neutron imaging experiment was carried out with a low flux neutron beam. Detection efficiency of 33% was achieved with only one doped MCP. The spatial resolution of 72μ m RMS is currently limited by the readout anode. A detector with larger area and improved readout method is now being developed.     

Preliminary attempt on maximum likelihood tomosynthesis reconstruction of DEI data

Tomosynthesis is a three-dimension reconstruction method that can remove the effect of superim- position with limited angle projections. It is especially promising in mammography where radiation dose is concerned. In this paper, we propose a maximum likelihood tomosynthesis reconstruction algorithm （ML-TS） on the apparent absorption data of diffraction enhanced imaging （DEI）. The motivation of this contribution is to develop a tomosynthesis algorithm in low-dose or noisy circumstances and make DEI get closer to clinic application. The theoretical statistical models of DEI data in physics are analyzed and the proposed algorithm is validated with the experimental data at the Beijing Synchrotron Radiation Facility （BSRF）. The results of ML-TS have better contrast compared with the well known ＇shift-and-add＇ algorithm and FBP algorithm.     

Electron beam density imaging system at Beam study using a portable slit the Shanghai Electron Ion Trap

In this work, a portable slit imaging system is developed to study both the electron beam diameter and the profile of the newly developed Shanghai Electron Beam Ion Trap （Shanghai EBIT）. Images are detected by a charge coupled device （CCD） sensitive to both X rays and longer wavelength photons （up to visible）. Large scale ray tracings were conducted for correcting the image broadening effects caused by the finite slit width and the finite width of the CCD pixels. A numerical de-convolution method was developed to analyse and reconstruct the electron beam density distribution in the EBIT. As an example of the measured beam diameter and current density, the FWHM （full width at half maximum） diameter of the electron beam at 81 keV and 120 mA is found to be 76.2 μm and the density 2.00 × 10^3 A.cm-2, under a magnetic field of 3 T, including all corrections.     

Polynomial curve fitting method for refraction-angle extraction in diffraction enhanced imaging

X-ray diffraction sorbing low-Z sample. How enhanced imaging （DEI） is applied to extract phase information from to inspect internal structures of weakly abraw images measured in different positions of rocking curve is the key problem of DEI. In this paper, we present an effective extraction method called polynomial curve fitting method, in order to extract accurate information angular in a fast speed. It is compared with the existing methods such as multiple-images statistical method and Gaussian curve fitting method. The experiments results on a plastic cylinder and a black ant at the Beijing Synchrotron Radiation Facility prove that the polynomial curve fitting method can obtain most approximate refraction-angle values and its computation speed is 10 times faster than the Gaussian curve fitting method.