scholarly journals Improved Reconstruction Quality of Bioluminescent Images by Combining SP3Equations and Bregman Iteration Method

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Qiang Wu ◽  
Jinchao Feng ◽  
Kebin Jia ◽  
Xiangyu Wang
Keyword(s):  
Drug Development ◽  
Iteration Method ◽  
Tumor Therapy ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Bregman Iteration ◽  
Bioluminescence Tomography ◽  
Practical Applications ◽  
Reconstruction Quality

Bioluminescence tomography (BLT) has a great potential to provide a powerful tool for tumor detection, monitoring tumor therapy progress, and drug development; developing new reconstruction algorithms will advance the technique to practical applications. In the paper, we propose a BLT reconstruction algorithm by combining SP3equations and Bregman iteration method to improve the quality of reconstructed sources. The numerical results for homogeneous and heterogeneous phantoms are very encouraging and give significant improvement over the algorithms without the use of SP3equations and Bregman iteration method.

scholarly journals Source reconstruction for bioluminescence tomography via L1∕2 regularization

2018 ◽  
Vol 11 (02) ◽  
pp. 1750014 ◽  
Author(s):  
Jingjing Yu ◽  
Qiyue Li ◽  
Haiyu Wang
Keyword(s):  
Image Quality ◽  
Matching Pursuit ◽  
Imaging Modality ◽  
Reconstruction Algorithm ◽  
Reconstruction Method ◽  
Reconstruction Algorithms ◽  
Preclinical Research ◽  
Bioluminescence Tomography ◽  
Comparison Results ◽  
Stable Reconstruction

Bioluminescence tomography (BLT) is an important noninvasive optical molecular imaging modality in preclinical research. To improve the image quality, reconstruction algorithms have to deal with the inherent ill-posedness of BLT inverse problem. The sparse characteristic of bioluminescent sources in spatial distribution has been widely explored in BLT and many L1-regularized methods have been investigated due to the sparsity-inducing properties of L1 norm. In this paper, we present a reconstruction method based on L[Formula: see text] regularization to enhance sparsity of BLT solution and solve the nonconvex L[Formula: see text] norm problem by converting it to a series of weighted L1 homotopy minimization problems with iteratively updated weights. To assess the performance of the proposed reconstruction algorithm, simulations on a heterogeneous mouse model are designed to compare it with three representative sparse reconstruction algorithms, including the weighted interior-point, L1 homotopy, and the Stagewise Orthogonal Matching Pursuit algorithm. Simulation results show that the proposed method yield stable reconstruction results under different noise levels. Quantitative comparison results demonstrate that the proposed algorithm outperforms the competitor algorithms in location accuracy, multiple-source resolving and image quality.

scholarly journals Compressed sensing for electrocardiogram acquisition in wireless body sensor network: A comparative analysis

2019 ◽  
Vol 15 (7) ◽  
pp. 155014771986488 ◽  
Author(s):  
Junxin Chen ◽  
Jiazhu Xing ◽  
Leo Yu Zhang ◽  
Lin Qi
Keyword(s):  
Compressed Sensing ◽  
Sensor Network ◽  
Low Cost ◽  
Reconstruction Algorithm ◽  
Signal Acquisition ◽  
Reconstruction Algorithms ◽  
Practical Applications ◽  
Body Sensor Network ◽  
The Past ◽  
Electrocardiogram Signals

In the past decades, compressed sensing emerges as a promising technique for signal acquisition in low-cost sensor networks. For prolonging the monitoring duration of biosignals, compressed sensing is also exploited for simultaneous sampling and compression of electrocardiogram signals in the wireless body sensor network. This article presents a comprehensive analysis of compressed sensing for electrocardiogram acquisition. The performances of involved important factors, such as wavelet basis, overcomplete dictionaries, and the reconstruction algorithms, are comparatively illustrated, with the purpose to give data reference for practical applications. Drawn from a bulk of comparative experiments, the potential of compressed sensing in electrocardiogram acquisition is evaluated in different compression levels, while preferred sparsifying basis and reconstruction algorithm are also suggested. Relative perspectives and discussions are also given.

scholarly journals Image reconstruction algorithm based on variable atomic number matching pursuit

2016 ◽  
Vol 11 (2) ◽  
pp. 103-109
Author(s):  
Hongtu Zhao ◽  
Chong Chen ◽  
Chenxu Shi
Keyword(s):  
Image Reconstruction ◽  
Convex Optimization ◽  
Atomic Number ◽  
Matching Pursuit ◽  
Greedy Algorithms ◽  
Optimization Algorithms ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Reconstruction Quality ◽  
Stable Reconstruction

As the most critical part of compressive sensing theory, reconstruction algorithm has an impact on the quality and speed of image reconstruction. After studying some existing convex optimization algorithms and greedy algorithms, we find that convex optimization algorithms should possess higher complexity to achieve higher reconstruction quality. Also, fixed atomic numbers used in most greedy algorithms increase the complexity of reconstruction. In this context, we propose a novel algorithm, called variable atomic number matching pursuit, which can improve the accuracy and speed of reconstruction. Simulation results show that variable atomic number matching pursuit is a fast and stable reconstruction algorithm and better than the other reconstruction algorithms under the same conditions.

A Modified Regularized Super-Resolution Reconstruction Algorithm

2014 ◽  
Vol 989-994 ◽  
pp. 2250-2253
Author(s):  
Qi Xie ◽  
Wei Yi Chen
Keyword(s):  
Detection System ◽  
Super Resolution ◽  
Reconstruction Algorithm ◽  
Modulation Transfer ◽  
Resolution Observation ◽  
Reconstruction Quality ◽  
Objective Indicators ◽  
Regularized Method ◽  
Optical Detection System

The super-resolution reconstruction technology is proposed in this paper to overcome the image degradation of shipboard optical detection system. Firstly, establish the super-resolution observation model, then analysis the inadequate of traditional regularized method through the modulation transfer function and proposed a modified regularized algorithm, experimental results shows that the proposed method has the better visual effect and objective indicators. It is a feasible method to enhance reconstruction quality of the system.

scholarly journals A semi-analytical solution and AI-based reconstruction algorithms for magnetic particle tracking

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0254051
Author(s):  
Huixuan Wu ◽  
Pan Du ◽  
Rohan Kokate ◽  
Jian-Xun Wang
Keyword(s):  
Analytical Solution ◽  
Particle Tracking ◽  
Magnetic Particle ◽  
Reconstruction Algorithm ◽  
Reconstruction Algorithms ◽  
Velocity Signal ◽  
Practical Applications ◽  
Sensor Arrangement ◽  
Traditional Approaches ◽  
Wavelet Methods

Magnetic particle tracking is a recently developed technology that can measure the translation and rotation of a particle in an opaque environment like a turbidity flow and fluidized-bed flow. The trajectory reconstruction usually relies on numerical optimization or filtering, which involve artificial parameters or thresholds. Existing analytical reconstruction algorithms have certain limitations and usually depend on the gradient of the magnetic field, which is not easy to measure accurately in many applications. This paper discusses a new semi-analytical solution and the related reconstruction algorithm. The new method can be used for an arbitrary sensor arrangement. To reduce the measurement uncertainty in practical applications, deep neural network (DNN)-based models are developed to denoise the reconstructed trajectory. Compared to traditional approaches such as wavelet-based filtering, the DNN-based denoisers are more accurate in the position reconstruction. However, they often over-smooth the velocity signal, and a hybrid method that combines the wavelet and DNN model provides a more accurate velocity reconstruction. All the DNN-based and wavelet methods perform well in the orientation reconstruction.

scholarly journals Variable Weighted Ordered Subset Image Reconstruction Algorithm

2006 ◽  
Vol 2006 ◽  
pp. 1-7 ◽  
Author(s):  
Jinxiao Pan ◽  
Tie Zhou ◽  
Yan Han ◽  
Ming Jiang
Keyword(s):  
Numerical Simulation ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Ct Data ◽  
Simultaneous Algebraic Reconstruction Technique ◽  
Algebraic Reconstruction

We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively.

scholarly journals A Finite Element Mesh Aggregating Approach to Multiple-Source Reconstruction in Bioluminescence Tomography

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Jingjing Yu ◽  
Fang Liu ◽  
L. C. Jiao ◽  
Shuyuan Yang ◽  
Xiaowei He
Keyword(s):  
Finite Element ◽  
A Priori ◽  
Finite Element Mesh ◽  
Reconstruction Algorithms ◽  
Multiple Sources ◽  
Element Mesh ◽  
Reconstruction Process ◽  
Bioluminescence Tomography ◽  
Process Reconstruction

A finite element mesh aggregating approach is presented to reconstruct images of multiple internal bioluminescence sources. Rather than assuming independence between mesh nodes, the proposed reconstruction strategy exploits spatial structure of nodes and aggregation feature of density distribution on the finite element mesh to adaptively determine the number of sources and to improve the quality of reconstructed images. With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power.

scholarly journals Preprocessing of Ion Microtomography Data for Improved Reconstruction Quality

1990 ◽  
Vol 217 ◽  
Author(s):  
David L. Weirup ◽  
Arthur E. Pontau ◽  
Arlyn J. Antolak ◽  
Dan H. Morse ◽  
G. Bench ◽  
...  
Keyword(s):  
Mechanical Stability ◽  
Center Of Mass ◽  
Reconstruction Algorithm ◽  
Spatial Filter ◽  
Mass Motion ◽  
Ion Energy ◽  
Reconstruction Quality ◽  
Micron Size ◽  
Pass Through

ABSTRACTIn Ion Microtomography (IMT), material densities are determined from the energy lost by ions as they pass through a specimen. For fine-scale measurements with micron-size beams, mechanical stability and precision of motion can impact the quality of the reconstruction. We describe several preprocessing procedures used to minimize imperfect specimen manipulation, including adjustment of the center of mass motion in sinograms and correction for vertical translations. In addition, the amount of noise in the reconstruction is reduced by utilizing median (as opposed to mean) ion energy loss values for density determinations. Furthermore, particular portions of the sampled image can be enhanced with minimal degradation of spatial resolution by a judicial choice of spatial filter in the reconstruction algorithm. The benefits and limitations of these preprocessing techniques are discussed.

Single Image Dehazing by Predicting Atmospheric Scattering Parameters

2020 ◽  
Vol 2020 (1) ◽  
pp. 74-77
Author(s):  
Simone Bianco ◽  
Luigi Celona ◽  
Flavio Piccoli
Keyword(s):  
Reference Image ◽  
Single Image ◽  
Scattering Parameters ◽  
Image Dehazing ◽  
Atmospheric Scattering ◽  
Local Structures ◽  
Full Reference ◽  
Reconstruction Quality ◽  
Single Image Dehazing

In this work we propose a method for single image dehazing that exploits a physical model to recover the haze-free image by estimating the atmospheric scattering parameters. Cycle consistency is used to further improve the reconstruction quality of local structures and objects in the scene as well. Experimental results on four real and synthetic hazy image datasets show the effectiveness of the proposed method in terms of two commonly used full-reference image quality metrics.

A unified framework for automated person re-indentification

2020 ◽  
Vol 71 (7) ◽  
pp. 868-880
Author(s):  
Nguyen Hong-Quan ◽  
Nguyen Thuy-Binh ◽  
Tran Duc-Long ◽  
Le Thi-Lan
Keyword(s):  
Deep Learning ◽  
Video Analysis ◽  
Camera Network ◽  
Unified Framework ◽  
Person Detection ◽  
Practical Applications ◽  
Detection And Tracking ◽  
Analysis System ◽  
Bounding Boxes

Along with the strong development of camera networks, a video analysis system has been become more and more popular and has been applied in various practical applications. In this paper, we focus on person re-identification (person ReID) task that is a crucial step of video analysis systems. The purpose of person ReID is to associate multiple images of a given person when moving in a non-overlapping camera network. Many efforts have been made to person ReID. However, most of studies on person ReID only deal with well-alignment bounding boxes which are detected manually and considered as the perfect inputs for person ReID. In fact, when building a fully automated person ReID system the quality of the two previous steps that are person detection and tracking may have a strong effect on the person ReID performance. The contribution of this paper are two-folds. First, a unified framework for person ReID based on deep learning models is proposed. In this framework, the coupling of a deep neural network for person detection and a deep-learning-based tracking method is used. Besides, features extracted from an improved ResNet architecture are proposed for person representation to achieve a higher ReID accuracy. Second, our self-built dataset is introduced and employed for evaluation of all three steps in the fully automated person ReID framework.

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