scholarly journals Nonlocal Total Variation Using the First and Second Order Derivatives and Its Application to CT image Reconstruction

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3494
Author(s):  
Yongchae Kim ◽  
Hiroyuki Kudo
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Second Order ◽  
Ct Image ◽  
Low Contrast ◽  
New Class ◽  
Nonlocal Total Variation ◽  
Intensity Changes ◽  
Adequate Image Quality ◽  
The Cost

We propose a new class of nonlocal Total Variation (TV), in which the first derivative and the second derivative are mixed. Since most existing TV considers only the first-order derivative, it suffers from problems such as staircase artifacts and loss in smooth intensity changes for textures and low-contrast objects, which is a major limitation in improving image quality. The proposed nonlocal TV combines the first and second order derivatives to preserve smooth intensity changes well. Furthermore, to accelerate the iterative algorithm to minimize the cost function using the proposed nonlocal TV, we propose a proximal splitting based on Passty’s framework. We demonstrate that the proposed nonlocal TV method achieves adequate image quality both in sparse-view CT and low-dose CT, through simulation studies using a brain CT image with a very narrow contrast range for which it is rather difficult to preserve smooth intensity changes.

scholarly journals Evolution from total variation to nonlinear sparsifying transform for sparse-view CT image reconstruction

2019 ◽  
Author(s):  
Jian Dong ◽  
Chunxiao Han ◽  
Zhuanping Qin ◽  
Yanqiu Che
Keyword(s):  
Image Reconstruction ◽  
Image Quality ◽  
Total Variation ◽  
Ct Images ◽  
Difficult Problem ◽  
Ct Image ◽  
Body Parts ◽  
Reconstruction Algorithms ◽  
Intensity Changes ◽  
Ct Image Reconstruction

AbstractSparse-view CT has been widely studied as an effective strategy for reducing radiation dose to patients. However, the conventional image reconstruction algorithms, such as filtered back-projection method and classical algebraic reconstruction techniques, can no longer be competent in the image reconstruction task of sparse-view CT. A new principle, called compressed sensing (CS), has been therefore developed to provide an effective solution for the ill-posed inverse problem of sparse-view CT image reconstruction. Total variation (TV) minimization, which is most extensively studied among the existing CS techniques, has been recognized as a powerful tool for dealing with this difficult problem in image reconstruction community. However, in recent years, the drawbacks of TV are being increasingly reported, which are appearance of patchy artifacts, depict of incorrect object boundaries, and loss in image textures or smooth intensity changes. These degradations appear especially in reconstructing actual CT images with complicated intensity changes. In order to address these drawbacks, a series of advanced algorithms using nonlinear sparsifying transform (NLST) have been proposed very recently. The NLST-based CS is based on a different framework from the TV, and it achieves an improvement in image quality. Since it is a relatively newly proposed idea, within the scope of our knowledge, there exist few literatures that discusses comprehensively how the image quality improvement occurs in comparison with the conventional TV method. In this study, we investigated the image quality differences between the conventional TV minimization and the NLST-based CS, as well as image quality differences among different kinds of NLST-based CS algorithms in the sparse-view CT image reconstruction. More specifically, image reconstructions of actual CT images of different body parts were carried out to demonstrate the image quality differences.

MO-FG-204-07: Nonlocal Total Variation Based Spectral CT Image Reconstruction

2015 ◽  
Vol 42 (6Part29) ◽  
pp. 3570-3570 ◽  
Author(s):  
J Liu ◽  
H Ding ◽  
S Molloi ◽  
X Zhang ◽  
H Gao
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Ct Image ◽  
Spectral Ct ◽  
Nonlocal Total Variation ◽  
Ct Image Reconstruction

scholarly journals Image Deconvolution with Hybrid Reweighted Adaptive Total Variation (HRATV) for Optoacoustic Tomography

Photonics ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 25
Author(s):  
Chen Yang ◽  
Yang Jiao ◽  
Xiaohua Jian ◽  
Yaoyao Cui
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Imaging Modality ◽  
Standard Test ◽  
Image Deconvolution ◽  
Low Contrast ◽  
Limited Bandwidth ◽  
Optoacoustic Tomography ◽  
Adaptive Total Variation

Optoacoustic tomography (OAT) is a hybrid biomedical imaging modality that usually employs a transducer array to detect laser-generated ultrasonic signals. The reconstructed image suffers low contrast and degraded resolution due to the limited bandwidth and the spatial directivity of the transducer element. Here, we introduce a modified image deconvolution method with a hybrid reweighted adaptive total variation tailored to improve the image quality of OAT. The effectiveness and the parameter dependency of the proposed method are verified on standard test images. The performance of the proposed method in OAT is then characterized on both simulated phantoms and in vivo mice experiments, which demonstrates that the modified deconvolution algorithm is able to restore the sharp edges and fine details in OAT simultaneously. The signal-to-noise ratios (SNRs) of the target structures in mouse liver and brain were improved by 4.90 and 12.69 dB, respectively. We also investigated the feasibility of using Fourier ring correlation (FRC) as an indicator of the image quality to monitor the deconvolution progress in OAT. Based on the experimental results, a practical guide for image deconvolution in OAT was summarized. We anticipate that the proposed method will be a promising post-processing tool to enhance the visualization of micro-structures in OAT.

A Systematic Review of Double Low-dose CT Pulmonary Angiography in Pulmonary Embolism

2019 ◽  
Vol 15 (5) ◽  
pp. 453-460 ◽  
Author(s):  
Sultan Aldosari ◽  
Zhonghua Sun
Keyword(s):  
Systematic Review ◽  
Pulmonary Embolism ◽  
Image Quality ◽  
Radiation Dose ◽  
Contrast Medium ◽  
Low Dose ◽  
Pulmonary Angiography ◽  
Ct Pulmonary Angiography ◽  
Low Contrast ◽  
Low Contrast Medium

Background: The aim of this study is to perform a systematic review of the feasibility and clinical application of double low-dose CT pulmonary angiography (CTPA) in the diagnosis of patients with suspected pulmonary embolism. Discussion: A total of 13 studies were found to meet selection criteria reporting both low radiation dose (70 or 80 kVp versus 100 or 120 kVp) and low contrast medium dose CTPA protocols. Lowdose CTPA resulted in radiation dose reduction from 29.6% to 87.5% in 12 studies (range: 0.4 to 23.5 mSv), while in one study, radiation dose was increased in the dual-energy CT group when compared to the standard 120 kVp group. CTPA with use of low contrast medium volume (range: 20 to 75 ml) was compared to standard CTPA (range: 50 to 101 ml) in 12 studies with reduction between 25 and 67%, while in the remaining study, low iodine concentration was used with 23% dose reduction achieved. Quantitative assessment of image quality (in terms of signal-to-noise ratio and contrast-to-noise ratio) showed that low-dose CTPA was associated with higher, lower and no change in image quality in 3, 3 and 6 studies, respectively when compared to the standard CTPA protocol. The subjective assessment indicated similar image quality in 11 studies between low-dose and standard CTPA groups, and improved image quality in 1 study with low-dose CTPA. Conclusion: This review shows that double low-dose CTPA is feasible in the diagnosis of pulmonary embolism with significant reductions in both radiation and contrast medium doses, without compromising diagnostic image quality.

SYNTHESIS OF BROADBAND DISTRIBUTED IMPEDANCE TRANSFORMERS WITH A GIVEN PHASE RESPONSE

2018 ◽  
pp. 40-47
Author(s):  
D. I. Volkhin ◽  
G. N. Devyatkov
Keyword(s):  
Transmission Lines ◽  
Conversion Coefficient ◽  
Power Conversion ◽  
Response Characteristic ◽  
Second Order ◽  
Phase Response ◽  
Synthesis Process ◽  
New Class ◽  
Broadband Matching ◽  
Active Impedance

The development of a new class of broadband matching devices, including active impedance transformers, with the possibility of correcting the phase response is an actual task at present. Synthesis of a broadband active impedance transformer with a phase response corresponding to a second-order lattice X-section in a distributed elemental basis based on the previously presented method for the synthesis of broadband matching devices with predetermined phase response is considered in this paper. As a result of synthesis, the y-matrix of the broadband transforming two-port network is obtained. The functions of its own parameters represented in the form of Foster. Applying various conditions of circuit realizability in the synthesis process, we obtained structures convenient for realization on microwave on regular transmission lines, one of which is investigated at various parameters of a given phase response. As a result of the research, it is found that the structure has a wide ability to reproduce the phase response of a second-order lattice X-section with different parameters, and also reproduce the linear phase response characteristic while maintaining an acceptable level of the power conversion coefficient in a given frequency band. Thus, the efficiency of the previously proposed method of synthesis of broadband matching devices with predetermined phase response is demonstrated, and also the possibilities of active impedance transformers on regular transmission lines are shown.

scholarly journals Fixed point theorems via Generalized WF-Contractions with applications

SeMA Journal ◽  
2021 ◽  
Author(s):  
Rosana Rodríguez-López ◽  
Rakesh Tiwari
Keyword(s):  
Fixed Point ◽  
Differential Equations ◽  
Boundary Value Problem ◽  
Fixed Point Theorems ◽  
Boundary Value ◽  
Second Order ◽  
Point Boundary ◽  
New Class ◽  
Second Order Differential Equations ◽  
Fixed Point Result

AbstractThe aim of this paper is to introduce a new class of mixed contractions which allow to revise and generalize some results obtained in [6] by R. Gubran, W. M. Alfaqih and M. Imdad. We also provide an example corresponding to this class of mappings and show how the new fixed point result relates to the above-mentioned result in [6]. Further, we present an application to the solvability of a two-point boundary value problem for second order differential equations.

scholarly journals Performance Evaluation of Dorsal Vein Network of Hand Imaging Using Relative Total Variation-Based Regularization for Smoothing Technique in a Miniaturized Vein Imaging System: A Pilot Study

2021 ◽  
Vol 18 (4) ◽  
pp. 1548 ◽  
Author(s):  
Kyuseok Kim ◽  
Hyun-Woo Jeong ◽  
Youngjin Lee
Keyword(s):  
Image Quality ◽  
Total Variation ◽  
Near Infrared ◽  
Imaging System ◽  
Histogram Equalization ◽  
Evaluation Performance ◽  
Visual Evaluation ◽  
Évaluation Performance ◽  
Nir Imaging ◽  
Relative Total Variation

Vein puncture is commonly used for blood sampling, and accurately locating the blood vessel is an important challenge in the field of diagnostic tests. Imaging systems based on near-infrared (NIR) light are widely used for accurate human vein puncture. In particular, segmentation of a region of interest using the obtained NIR image is an important field, and research for improving the image quality by removing noise and enhancing the image contrast is being widely conducted. In this paper, we propose an effective model in which the relative total variation (RTV) regularization algorithm and contrast-limited adaptive histogram equalization (CLAHE) are combined, whereby some major edge information can be better preserved. In our previous study, we developed a miniaturized NIR imaging system using light with a wavelength of 720–1100 nm. We evaluated the usefulness of the proposed algorithm by applying it to images acquired by the developed NIR imaging system. Compared with the conventional algorithm, when the proposed method was applied to the NIR image, the visual evaluation performance and quantitative evaluation performance were enhanced. In particular, when the proposed algorithm was applied, the coefficient of variation was improved by a factor of 15.77 compared with the basic image. The main advantages of our algorithm are the high noise reduction efficiency, which is beneficial for reducing the amount of undesirable information, and better contrast. In conclusion, the applicability and usefulness of the algorithm combining the RTV approach and CLAHE for NIR images were demonstrated, and the proposed model can achieve a high image quality.

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