This paper concerns iterative reconstruction for low-dose and few-view CT by minimizing a data-fidelity term regularized with the Total Variation (TV) penalty. We propose a very fast iterative algorithm to solve this problem. The algorithm derivation is outlined as follows. First, the original minimization problem is reformulated into the saddle point (primal-dual) problem by using the Lagrangi...

Objective To describe the quantitative image quality and histogram-based evaluation of an iterative reconstruction (IR) algorithm in chest computed tomography (CT) scans at low-to-ultralow CT radiation dose levels. Materials and Methods In an adult anthropomorphic phantom, chest CT scans were performed with 128-section dual-source CT at 70, 80, 100, 120, and 140 kVp, and the reference (3.4 mG...

Abstract Purpose Phantom studies in CT emphysema quantification show that iterative reconstruction and deep learning-based noise reduction (DLNR) allow lower radiation dose. We compared on ultra-low-dose (ULDCT) with without reduction, to standard-dose (SDCT) chronic obstructive pulmonary disease (COPD). Method Forty-nine COPD patients underwent ULDCT (third generation dual-source CT; 70ref-mAs...

Bright Field (BF) electron tomography (ET) has been widely used in the life sciences to characterize biological specimens in 3D. While BF-ET is the dominant modality in the life sciences it has been generally avoided in the physical sciences due to anomalous measurements in the data due to a phenomenon called “Bragg scatter” visible when crystalline samples are imaged. These measurements cause ...

introduction:  the  purpose  of  this  study  is  to  define  the  optimal  parameters  for  the  tomographic  reconstruction procedure in a routine single photon emission tomography. the hoffman brain phantom  is modified to evaluate the reconstruction method. the phantom was imaged in a 3 and 2-dimensional  conformation and the results were compared.   materials  and  methods:  the  2d  phant...

We propose the Forward-Backward Synergistic Acceleration Pursuit (FBSAP) algorithm in this paper. The FBSAP algorithm inherits the advantages of the Forward-Backward Pursuit (FBP) algorithm, which has high success rate of reconstruction and does not necessitate the sparsity level as a priori condition. Moreover, it solves the problem of FBP that the atom can be selected only by the fixed step s...

PURPOSE The influence of the numbers of projection of SPECT exerting on a re-constructed image cannot be strictly evaluated by phantom studies. Therefore, we compared re-constructed images of the FBP method and the ML-EM method by using simulation data. METHODS Simulation data was entered in the image processing software, and the projection data that changed the numbers of projection was made...

OBJECTIVE To evaluate the image quality produced by six different iterative reconstruction (IR) algorithms in four CT systems in the setting of brain CT, using different radiation dose levels and iterative image optimisation levels. METHODS An image quality phantom, supplied with a bone mimicking annulus, was examined using four CT systems from different vendors and four radiation dose levels...

For spiral cone-beam CT, parallel computing is an effective approach to resolving the problem of heavy computation burden. It is well known that the major computation time is spent in the backprojection step for either filtered-backprojection (FBP) or backprojected-filtration (BPF) algorithms. By the cone-beam cover method [1], the backprojection procedure is driven by cone-beam projections, an...

An ordered subsets expectation maximization (OS-EM) algorithm is used for image reconstruction to suppress image noise and to make non-negative value images. We have applied OS-EM to a digital brain phantom and to human brain 18F-FDG PET kinetic studies to generate parametric images. A 45 min dynamic scan was performed starting injection of FDG with a 2D PET scanner. The images were reconstruct...