Abstract Three-dimensional particle reconstruction with limited two-dimensional projections is an under-determined inverse problem that the exact solution often difficult to be obtained. In general, approximate solutions can obtained by iterative optimization methods. current work, a practical method based on convolutional neural network (CNN) geometry-informed features proposed. The proposed t...

A method for optimizing image-recovery algorithms is presented that is based on how well a specified visual task can be performed using the reconstructed images. Visual task performance is numerically assessed by a Monte Carlo simulation of the complete imaging process including the generation of scenes appropriate to the desired application, subsequent data taking, image recovery, and performa...

The Computer Tomography (CT) method is used for remote sensing the Earth’s plasmasphere. One challenge image reconstruction insufficient projection data, mainly caused by limited angles. In this study, we apply Algebraic Reconstruction Technique (ART) and minimization of Total Variation (TV) method, with a combination priori knowledge north–south symmetry, to reconstruct plasmaspheric He+<...

In this paper we propose an algebraic full multigrid algorithm for efficient and robust numerical solution of arbitrary linear systems of equations arising in image reconstruction from projections in computerized tomography. Numerical experiments and comparisons with the classical Kaczmarz algebraic reconstruction technique are presented.

The recently presented sequential unconstrained minimization algorithm SUMMA is extended to provide a framework for the derivation of block-iterative, or partial-gradient, optimization methods. This BI-SUMMA includes, and is motivated by, block-iterative versions of the algebraic reconstruction technique (ART) and its multiplicative variant, the MART. The BI-SUMMA approach is designed to provid...

The problem of image reconstruction from projections in computerized tomography, when cast as a system of linear equations, leads to an inconsistent system. The problem is studied under very adverse conditions, consisting of lowcontrast images and a strongly underdetermined system, where the number of equations is only about 25% of the number of variables (fewer equations enable the use of less...

The Common Unified Device Architecture (CUDA) introduced in 2007 by NVIDIA is a recent programming model making use of the unified shader design of the most recent graphics processing units (GPUs). The programming interface allows algorithm implementation using standard C language along with a few extensions without any knowledge about graphics programming using OpenGL, DirectX, and shading lan...

Image reconstruction is an important task in X-ray computed tomography. In this paper we discuss the results of morphological analysis of test objects in high-noise conditions and compare image reconstruction using two widely employed methods in computed tomography, namely Filtered Back Projection and Algebraic Reconstruction Technique. In our test tomography experiments, we used a laboratory X...

It is widely recognised that the most popular manner of image representation is obtained by using an energy-preserving transform, like the Fourier transform. However, since the advent of computerised tomography in the 70s, another manner of image representation has also entered the center of interest. This new type is the projection space representation, obtained via the Radon transform. Method...

This paper examines the use of the Algebraic Reconstruction Method (ART) and related techniques to reconstruct 3D objects from a relatively sparse set of cone-beam projection data. Although ART has been widely used for cone-beam reconstruction of high-contrast objects, e.g. in computed angiography, we are interested in the more challenging low-contrast case which represents a little investigate...