New Method Of Image Reconstruction Research Articles

Реконструкция пространственного распределения источников излучения в пропорциональной рассеивающей среде

A new method of image reconstruction for single-photon emission computed tomography in a proportional scattering medium is investigated. The detector counts were obtained using Monte Carlo simulation with the Geant4 nuclear physics software system, which eliminates the need for a real tomograph, radiopharmaceuticals and a phantom under study. In this case, the detector counts obtained with the Geant4 do not practically differ from those that would have been obtained in a full-scale experiment for the real scattering medium. The influence of the absorbing and scattering properties of thirteen different substances as a medium, in which the spatial distribution of radiation sources is immersed, on the accuracy of the tomogram reconstruction is investigated. The significant advantage of the proposed algorithm for reconstruction of emission tomograms in comparison with the traditional one is shown.

Novel Deep Level Image State Ensemble Enhancement Method for M87 Imaging

Standard spatial domain filters fail to adequately denoise and enhance the contrast of an image. These filters have drawbacks like oversmoothing, diminished texture, and lack of generative capabilities. This paper proposes a new method of image reconstruction, Image State Ensemble Enhancement (ISEE), based on our previous work, Image State Ensemble Decomposition (ISED). Deep level ISEE and ISED have been developed to produce a class of filters that can address these issues. Full-reference and no-reference quality metrics are used to assess the image, and the full reference metrics showed a marked improvement, while the no-reference metrics were often better than the test image. The test image was taken from the Spitzer Space Telescope (SST), and ISEE reconstruction yielded improved structural detail over that of ISED and the original test image. Glare and noise were reduced in a narrow bandwidth, which led to the discovery of a vortex-shaped structure and an outburst in M87′s dusty infrared core. The vortex is located over M87′s visible core and black hole. This is verified with an SST and Hubble Space Telescope (HST) overlay, ISEE processed image. A counter-jet channel was also discovered, and it appears to be the path of the unobservable superluminal counter-jet.

Image Reconstruction from Digital Holograms Obtained by Specifying Random Phase Shifts

A new method for image reconstruction from a series of digital holograms obtained by stepped phase shift with random values of phase shifts is under consideration. It is shown that images reconstructed from a digital hologram in a Fresnel region at a distance matching a distance from the object to the hologram consist of two parts, one of which is a clear image of the object and the other one being formed by incorrect phase shifts consists of a set of defocused images of the object. At the same time, the quality of the reconstructed image is slightly reduced. This effect eliminates the necessity to use precision systems for setting the phase shift and significantly reduces requirements for stabilizing the optical device.

Fluorescent molecular tomographic reconstruction via compensating for modelling error

ABSTRACTFluorescent molecular tomography (FMT) is emerging as a reliable optics-based molecular imaging technique. The diffusion approximation is commonly employed as a forward model for reconstruction. However, the diffusion equation is not valid in regions where the medium is low scattering or nonscattering. In addition, reconstruction based on the coarse grid will result in the low reconstruction accuracy although the computational requirements can be reduced. This paper is concerned with a new method of image reconstruction for FMT. In this method, the tomographic image of FMT is reconstructed in combination with the modelling error. Furthermore, an iterative strategy of grouped light sources is incorporated into the reconstruction process. The results attest that the proposed algorithm can speed up the reconstruction process and improve the quality of image reconstruction.

Image reconstruction based on circulant matrices

We propose a new method for image reconstruction based on circulant matrices. The novelty of this method is the image treatment using a simple and classical algebraic structure, the circulant matrix, which significantly reduces the computational effort, nevertheless providing reliable outputs. We compare the results with well established techniques such as the Principal Component Analysis (PCA) and the Discrete Fourier Transform (DFT), and the recently introduced Randomized Singular Value Decomposition (RSVD). We conclude that the quality is comparable whilst the computational time is considerably reduced.

CNN-Based Projected Gradient Descent for Consistent CT Image Reconstruction.

We present a new image reconstruction method that replaces the projector in a projected gradient descent (PGD) with a convolutional neural network (CNN). Recently, CNNs trained as image-to-image regressors have been successfully used to solve inverse problems in imaging. However, unlike existing iterative image reconstruction algorithms, these CNN-based approaches usually lack a feedback mechanism to enforce that the reconstructed image is consistent with the measurements. We propose a relaxed version of PGD wherein gradient descent enforces measurement consistency, while a CNN recursively projects the solution closer to the space of desired reconstruction images. We show that this algorithm is guaranteed to converge and, under certain conditions, converges to a local minimum of a non-convex inverse problem. Finally, we propose a simple scheme to train the CNN to act like a projector. Our experiments on sparse-view computed-tomography reconstruction show an improvement over total variation-based regularization, dictionary learning, and a state-of-the-art deep learning-based direct reconstruction technique.

Compressed-sensing-based fluorescence molecular tomographic image reconstruction with grouped sources.

BackgroundAlthough the quality of reconstructed results can be improved with the increment of the number of measurements, the scale of the matrices involved in the reconstruction of fluorescence molecular tomography (FMT) will become larger, which leads to the poor efficiency of the process of tomographic image reconstruction. In this paper, we proposed a new method for image reconstruction of FMT based on compressed sensing, in which a scheme of grouped sources is incorporated.MethodsThe forward equations are implemented using the finite element method (FEM). The reconstruction model is formulated under the framework of compressed sensing theory. The regularization term and the total variation penalty are incorporated in the objective function. During the reconstruction of FMT, the sources are divided into two groups for iteration in turn. One group of sources is employed in the first iteration of inverse problem, and the other group is employed in the next iteration.ResultsSimulation results demonstrate that the computation time and mean square error (MSE) of the reconstruction with our algorithm are less than those with the traditional method. The proposed algorithm can reconstruct the target with enhanced contrast and more accurate shape.ConclusionsThe proposed algorithm can significantly improve the speed and accuracy of the reconstruction of FMT. Furthermore, our compressed-sensing-based method can reduce the number of measurements.

Empirical determination of the temperature stratification in the photosphere of the quiet Sun

Context. Detailed realistic 3D simulations of the photosphere of the Sun are now available, but 1D models of the average quiet-Sun photosphere are still widely used, in particular for spectro-polarimetric inversions. Aims. Here we present an empirical determination of the average radiation temperature variations as a function of the geometrical height above the continuum formation level in the solar photosphere.Methods. We used high resolution spectroscopic scans in the 630 nm Fe i line pair at varying heliocentric angles along the north-south polar axis of the Sun, made with SOT onboard Hinode. Implementing a new method for image reconstruction, we obtained images of the photospheric granulation at constant continuum opacity levels, from the upper photosphere seen at line centers to the low photosphere. The Fourier cross-spectra of images at different opacity levels were computed, and we derived the formation depths of images without referring to any atmospheric model, by measuring the slope of the cross-spectrum phase. Results. A modified Milne-Eddington model for the line formation was tested by comparing it with the average line-intensity profiles observed at solar disk center. It yields consistent results for the FeI 630.2 nm line, whereas the FeI line at 630.1 nm is not well reproduced by the model. We ascribe this discrepancy to non-LTE effects in the line formation processes. The average image intensities at the different FeI 630.2 nm levels were used to determine the depth-variation of the temperature for an average 1D model of the quiet photosphere. We compared our empirical temperature model with the widely used FALC model. Both models agree well for the temperature variations with the continuum optical depth. But in the low photosphere, the temperature gradient we measure with respect to the geometrical height is significantly softer than in Model C. We argue that some of the assumptions used to solve the pseudohydrostatic equilibrium in semi-empirical models are probably at fault. We also derived empirical values for the 630 nm continuum absorption coefficient as a function of the geometrical height in the low photosphere. Finally, we were able to measure the altitude of the base of the granulation contrast inversion layer, which is found at about 130 km above the base of the photosphere, in agreement with 3D MHD simulations.

Construction function for three-dimensional sinograms of the time-of-flight positron emission tomograph

A new method of image reconstruction for the time-of-flight positron emission tomograph (TOF-PET) has been developed. A construction function was found to reconstruct a positron image by directly convoluting three-dimensional sinograms. This construction function consists of the product of the well-known function for a conventional PET and the response function of time-of-flight measurement system for annihilation γ rays.

Digital reconstruction of bright field phase contrast images from high resolution electron micrographs

The theory of bright-field image formation of thin specimens in a conventional transmission electron microscope is presented. The recorded image contrast is shown to be predominantly linear in the electron atom scattering amplitudes which are in general complex (possessing phase and amplitude). A linearized image model describing multiple images of varying defocus (defocus series) is derived. Image degradation is characterized by an instrumental transfer function (including spherical aberration, defocus and partial coherence), a finite signal-to-noise ratio and a Debye--Waller temperature factor. Using the minimum mean square error criterion, a new method of image reconstruction to recover the real and imaginary parts of the ideal phase contrast image from a defocus series is derived. This new method of image reconstruction reduces to the well known Wiener filter in the appropriate limiting conditions. A defocus series of micrographs taken on the Kyoto 500 keV electron microscope using a radiation damage resistant specimen of chlorinated copper phthalocyanine is processed. The signal-to-noise ratio of this series is found to be approximately 10. A resolution of approximately 2 A is apparent in the unprocessed images. The complex image reconstructed from this defocus series shows increased resolution in the real part of the image (approximately 1.4 A) and increased heavy/light atom contrast in the imaginary part of the image.

Digital reconstruction of bright field phase contrast images from high resolution electron micrographs

The theory of bright-field image formation of thin specimens in a conventional transmission electron microscope is presented. The recorded image contrast is shown to be predominantly linear in the electron atom scattering amplitudes which are in general complex (possessing phase and amplitude). A linearized image model describing multiple images of varying defocus (defocus series) is derived. Image degradation is characterized by an instrumental transfer function (including spherical aberration, defocus and partial coherence), a finite signal-to-noise ratio and a Debye—Waller temperature factor. Using the minimum mean square error criterion, a new method of image reconstruction to recover the real and imaginary parts of the ideal phase contrast image from a defocus series is derived. This new method of image reconstruction reduces to the well known Wiener filter in the appropriate limiting conditions. A defocus series of micrographs taken on the Kyoto 500 keV electron microscope using a radiation damage resistent specimen of chlorinated copper phthalocyanine is processed. The signal-to-noise ratio of this series is found to be approximately 10. A resolution of ∼2 Å is apparent in the unprocessed images. The complex image reconstructed from this defocus series shows increased resolution in the real part of the image (∼1.4 Å) and increased heavy/light atom contrast in the imaginary part of the image.