Journal of X-Ray Science and Technology - Volume 27, issue 3

Authors: Zhang, Yanbo | Salehjahromi, Morteza | Yu, Hengyong

Article Type: Research Article

Abstract: BACKGROUND As one type of the state-of-the-art detectors, photon counting detectors are used in spectral computed tomography (CT) to classify the received photons into several energy channels and generate multichannel projections simultaneously. However, FBP reconstructed images contain severe noise due to the low photon counts in each energy channel. OBJECTIVE A spectral CT image denoising method based on tensor-decomposition and non-local means (TDNLM) is proposed. METHODS In a CT image, it is widely accepted that there exists self-similarity over the spatial domain. In addition, because a multichannel CT image is obtained from the same object at …different energies, images among different channels are highly correlated. Motivated by these two characteristics of the spectral CT images, tensor decomposition and non-local means are employed to recover fine structures in spectral CT images. Moreover, images in all energy channels are added together to form a high signal-to-noise ratio image, which is applied to encourage the signal preservation of the TDNLM. The combination of TD, NLM and the guidance of a high-quality image enhances the low-dose spectral CT, and a parameter selection strategy is designed to achieve the optimal image quality. RESULTS The effectiveness of the developed algorithm is validated on both numerical simulations and realistic preclinical applications. The root mean square error (RMSE) and the structural similarity (SSIM) are used to quantitatively assess the image quality. The proposed method successfully restored high-quality images (average RMSE=0.0217 cm-1 and SSIM=0.987) from noisy spectral CT images (average RMSE=0.225 cm-1 and SSIM=0.633). In addition, RMSE of each decomposed material component is also remarkably reduced. Compared to the state-of-the-art iterative spectral CT reconstruction algorithms, the proposed method achieves comparable performance with dramatically reduced computational cost, resulting in a speedup of >50. CONCLUSIONS The outstanding denoising performance, the high computational efficiency and the adaptive parameter selection strategy make the proposed method practical for spectral CT applications. Show more

Keywords: Spectral computed tomography, noise estimation, non-local means, tensor decomposition

DOI: 10.3233/XST-180413

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 397-416, 2019

Authors: Bao, Nan | Li, Ang | Zhao, Wei | Cui, Zhiming | Tian, Xinhua | Yue, Yong | Li, Hong | Qian, Wei

Article Type: Research Article

Abstract: In the lung biopsy image-guided surgery systems, the fiducial markers are used for point-based registration of the patient space to the CT image space. Fiducial marker detection and fiducial point localization in CT images have great influence on the accuracy of registration and guidance. This study proposes a fiducial marker detection approach based on the features of marker image slice sequences and a fiducial point localization approach according to marker projection images, without depending on the priori-knowledge of the marker default parameters provided by the manufacturers. The accuracy of our method was validated based on a CT image dataset of …24 patients. The experimental results showed that all 144 markers of 24 patients were correctly detected, and the fiducial points were localized with the average error of 0.35 mm. In addition, the localization accuracy of the proposed method was improved by an average of 12.5% compared with the accuracy of the previous method using the marker default parameters provided by the manufacturers. Thus, the study demonstrated that the proposed detection and localization methods are accurate and robust, which is quite encouraging to meet the requirement of future clinical applications in the image guided lung biopsy and surgery systems. Show more

Keywords: Image-guided surgery, marker detection, fiducial point localization, CT image, point-based registration

DOI: 10.3233/XST-180464

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 417-429, 2019

Authors: Deng, Luzhen | Yasar, Selcuk | Ahmed, Md Foiez | Jayarathna, Sandun | Feng, Peng | Wei, Biao | Vedantham, Srinivasan | Karellas, Andrew | Cho, Sang Hyun

Article Type: Research Article

Abstract: OBJECTIVE: To investigate the image quality and x-ray dose associated with a transmission computed tomography (CT) component implemented within the same platform of an experimental benchtop x-ray fluorescence CT (XFCT) system for multimodal preclinical imaging applications. METHODS: Cone-beam CT scans were performed using an experimental benchtop CT + XFCT system and a cylindrically-shaped 3D-printed polymethyl methacrylate phantom (3 cm in diameter, 7 cm in height) loaded with various concentrations (0.05–1 wt. %) of gold nanoparticles (GNPs). Two commercial CT quality assurance phantoms containing 3D line-pair (LP) targets and contrast targets were also scanned. The x-ray beams of 40 and 62 kVp, both filtered by …0.08 mm Cu and 0.4 mm Al, were used with 17 ms of exposure time per projection at three current settings (2.5, 5, and 10 mA). The ordered-subset simultaneous algebraic reconstruction and total variation–minimization methods were used to reconstruct images. Sparse projection and short scan were considered to reduce the x-ray dose. The contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were calculated. RESULTS: The lowest detectable concentration of GNPs (CNR > 5) and the highest spatial resolution (per MTF50%) were 0.10 wt. % and 9.5 LP/CM, respectively, based on the images reconstructed from 360 projections of the 40 kVp beam (or x-ray dose of 3.44 cGy). The background noise for the image resulting in the lowest GNP detection limit was 25 Hounsfield units. CONCLUSION: The transmission CT component within the current experimental benchtop CT + XFCT system produced images deemed acceptable for multimodal (CT + XFCT) imaging purposes, with less than 4 cGy of x-ray dose. Show more

Keywords: Computed tomography, x-ray fluorescence computed tomography, x-ray dose, image resolution

DOI: 10.3233/XST-180457

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 431-442, 2019

Authors: Sun, Zong-Qiong | Hu, Shu-Dong | Shao, Lin | Jin, Lin-Fang | Lv, Qing | Li, Yao-Sen | Yan, Gen

Article Type: Research Article

Abstract: PURPOSE: To investigate associations between the clinicopathologic features and CT perfusion parameters of triple-negative breast cancer (TNBC) and non-TNBC using low-dose computed tomography perfusion imaging (LDCTPI), and to find potential clinical applications in the prognosis assessment of TNBC. MATERIALS AND METHODS: A total of 60 patients with breast cancer confirmed by pathological examination were studied prospectively using LDCTPI on a 64-slice spiral CT scanner. The acquired volume data were used for calculations, mapping, and analysis by using a tumor perfusion protocol in the CT perfusion software package to measure 2 parameters namely, blood flow (BF), and permeability surface …(PS) area product. Patients were grouped into TNBC (n  = 27) and non-TNBC (n  = 33) subtypes. Associations between these two subtypes and clinicopathologic characteristics were evaluated by both univariate and multivariate logistic regression. CT perfusion parameters values were compared for clinicopathologic characteristics using independent 2-sample t test. RESULTS: TNBC displayed higher CT perfusion parameters values (BF: 57.56±10.94 vs 52.70±7.79 mL/100 g/min, p  = 0.006; PS: 38.98±9.46 vs 33.39±8.07 mL/100 g/min, p  = 0.001) than non-TNBC. In addition, breast cancer with poorly histologic grade or positive Ki-67 expression showed higher BF and PS values than those with well and moderately histologic grade or negative Ki-67 expression (p  < 0.05). TNBC had poorer histologic grade (P  = 0.032) and higher Ki-67 expression (P  = 0.013) than non-TNBC. CONCLUSION: LDCTPI is a functional imaging technology from the perspective of hemodynamics with potential of clinical applications. The BF and PS values were higher in TNBC patient group than non-TNBC group. TNBC patients also have poorer clinicopathologic outcome. Show more

Keywords: Triple-negative breast cancer, clinicopathologic features, computed tomography, X-ray, perfusion, prognosis

DOI: 10.3233/XST-180465

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 443-451, 2019

Authors: Liu, Yang | Wu, Ketong | Lai, Haiyang | Zeng, Zhaofei | Zhang, Bo

Article Type: Research Article

Abstract: OBJECTIVE: To investigate the clinical efficacy and safety of fluoroscopic guided percutaneous antegrade ureteral stents placement used for treatment of malignant ureteral obstruction. METHODS: Between April 2016 and March 2018, fluoroscopic guided percutaneous ureteral stents was performed in 25 patients, including 7 patients (28%) with bilateral obstruction. The most common cancer diagnoses were cervical cancer (28%), rectal cancer (24%) and colon cancer (16%) among these patients. Clinical data were retrospectively analyzed with respect to the efficacy, safety and outcome of this treatment method. RESULTS: Percutaneous antegrade placement of ureteral stents was performed in all cases, including …12 ureters that failed in the initial retrograde ureteral stents placement. The median stent patency time for the antegrade ureteral stents were 10.4 (95% CI: 8.3–12.6) months. The primary complications included mild flank pain and discomfort (44%), hematuria (44%), urinary tract infection (8%), bladder irritation symptoms (4%), and arterial bleeding (4%). CONCLUSION: Fluoroscopic guided percutaneous ureteral stents placement is a safe, efficient procedure and has a high success rate in patients with malignant ureteral obstruction. Show more

Keywords: Malignant ureteral obstruction, ureteral stent, percutaneous antegrade, fluoroscopic

DOI: 10.3233/XST-180466

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 453-460, 2019

Authors: Wu, Xiaochuan | He, Peng | Long, Zourong | Guo, Xiaodong | Chen, Mianyi | Ren, Xuezhi | Chen, Peijun | Deng, Luzhen | An, Kang | Li, Pengcheng | Wei, Biao | Feng, Peng

Article Type: Research Article

Abstract: BACKGROUND: Spectral computed tomography (CT) has the capability to resolve the energy levels of incident photons, which has the potential to distinguish different material compositions. Although material decomposition methods based on x-ray attenuation characteristics have good performance in dual-energy CT imaging, there are some limitations in terms of image contrast and noise levels. OBJECTIVE: This study focused on multi-material decomposition of spectral CT images based on a deep learning approach. METHODS: To classify and quantify different materials, we proposed a multi-material decomposition method via the improved Fully Convolutional DenseNets (FC-DenseNets). A mouse specimen was first scanned …by spectral CT system based on a photon-counting detector with different energy ranges. We then constructed a training set from the reconstructed CT images for deep learning to decompose different materials. RESULTS: Experimental results demonstrated that the proposed multi-material decomposition method could more effectively identify bone, lung and soft tissue than the basis material decomposition based on post-reconstruction space in high noise levels. CONCLUSIONS: The new proposed approach yielded good performance on spectral CT material decomposition, which could establish guidelines for multi-material decomposition approaches based on the deep learning algorithm. Show more

Keywords: Spectral CT, photon-counting detector, material decomposition, deep learning

DOI: 10.3233/XST-190500

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 461-471, 2019

Authors: Wali, Lila | Helal, Azza | Darwesh, Reem | Attar, Mohammed

Article Type: Research Article

Abstract: BACKGROUND: Cervical cancer radiotherapy is usually administrated through 3-Dimensional Conformal Radiation Therapy (3DCRT) followed by a brachytherapy (BT) boost. PURPOSE: To investigate whether Volumetric Modulated Arc Therapy (VMAT) can replace High Dose Rate (HDR) intracavitary BT boost for patients undergoing cervical cancer radiotherapy. MATERIALS AND METHODS: Computed Tomography (CT) images for ten patients with tandem and ovoids were included in this study. Target volumes, rectum, bladder, sigmoid, small bowel and both femoral heads were delineated. Two plans were carried out including (a) a BT plan optimized manually by modifying dwell time and Ir-192 source positions, (b) …a VMAT plan generated using two partial arcs with 10 MV photon beam. The prescribed dose was 7 Gy. The relevant dose volume parameters (DVPs) of target volumes and OARs for the two plans were analyzed statistically using SPSS Wilcoxon Signed Rank test. RESULTS: VMAT plan showed a significant reduction of 9.1%, 9.3%, 15.4%, 14.4% and 13.1% in rectum maximum dose, rectum D2cc , bladder maximum dose, bladder D2cc and sigmoid maximum dose (P  < 0.05). VMAT and BT plans showed comparable D2cc of sigmoid and small bowel maximum doses (P  = 0.333 and P  = 0.646). On the other hand, VMAT showed significantly higher small bowel D2cc and maximum point dose for both femoral heads comparing to BT plan (P  < 0.05). Also, VMAT plan yielded greater homogeneous target coverage compared to BT plan (P  < 0.05). CONCLUSION: The study demonstrated that VMAT plan achieves significant dose reduction of rectum, bladder and sigmoid, as well as superior homogeneous target coverage compared to BT plan. On the other hand, VMAT delivers more radiation exposures to small bowel and femoral heads. Show more

Keywords: Cervical cancer, high dose rate, Volumetric Modulated Arc Therapy, intracavitary brachytherapy

DOI: 10.3233/XST-180468

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 473-483, 2019

Authors: Zhang, Hong-Xia | Sun, Zong-Qiong | Cheng, You-Gen | Mao, Guo-Qun

Article Type: Research Article

Abstract: PURPOSE: To explore the radiomics features of triple negative breast cancer (TNBC) and non-triple negative breast cancer (non-TNBC) based on X-ray mammography, and to differentiate the two groups of cases. MATERIALS AND METHODS: Preoperative mammograms of 120 patients with breast ductal carcinoma confirmed by surgical pathology were retrospectively analyzed, which include 30 TNBC and 90 non-TNBC patients. The manual segmentation of breast lesions was performed by ITK-SNAP software and 12 radiomics features were extracted by Omni-Kinetics software. The differences of these radiomics features between TNBC and non-TNBC groups were compared, and the receiver operating characteristic (ROC) curve was …used to determine the optimal cutoff value of each radiomics parameter for differentiating TNBC from non-TNBC, and the corresponding area under the curve (AUC), sensitivity and specificity were obtained. RESULTS: There were statistically significant differences for 4 radiomics features between TNBC and non-TNBC datasets (P  < 0.05). They were the roundness, concavity, gray average and skewness of breast lesions. Compared with non-TNBC, TNBC cases have following characteristics of (1) more round with the roundness of 0.621 vs. 0.413 (P  < 0.001), (2) more regular with the concavity of 0.087 vs. 0.141 (P  < 0.01), (3) higher density or gray average (67.261 vs. 56.842, P  < 0.05), and (4) lower skewness (– 0.837 vs.– 0.671, P  = 0.034). AUCs of ROC curves computed using features of the roundness and concavity were both larger than 0.70. CONCLUSION: Radiomics features based on X-ray mammography may be helpful to distinguish between TNBC and non-TNBC, which were associated with breast tumor histology. Show more

Keywords: Triple negative breast cancer, X-ray mammography, quantitative imaging markers, evaluation of tumor characteristics

DOI: 10.3233/XST-180488

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 485-492, 2019

Authors: Wang, Qian | Li, Erni | Song, Ying | Ma, Peiqing | Wang, Yipeng | Liu, Xia | Qi, Weiwei | Zhao, Xinming

Article Type: Research Article

Abstract: OBJECTIVE: To retrospectively explore correlation of the resected specimen volume of breast microcalcification lesions and endogenous and exogenous factors of stereotactic needle localization biopsy (SNLB). MATERIALS AND METHODS: Totally 214 patients underwent SNLB for non-palpable breast lesion with microcalcification lesions. Of 211 patients, 198 patients underwent single needle localization and 13 patients underwent multi-needle localization (26 lesions). Lesion sizes, distribution characteristics, lesion localization accuracy and resected specimen volumes were recorded and analyzed using a generalized linear model (GLM). RESULTS: The average lesion diameter is 2.63±1.73 cm. The localization accuracy of 187 lesions were moderate, 26 were too …deep and 11 were too superficial. The mean resected specimen volume (V) was 17.51±5.14 cm3 . One-way ANOVA analysis showed that 3 factors, including lesion sizes, distribution characteristics and the localization accuracy were associated with resected specimen volume (F = 67.56–112.78, P  < 0.001). GLM revealed that lesion sizes, single clustered distribution and accurate localization were significant factors for resected specimen volume (F = –4.82–11.36, P  < 0.05). The ratio (%) of the resected specimen volume to the involved breast volume (V0) was defined as the degree of breast defect. The mean breast defect of 125 benign patients (V/V0) was 27.5% ranging from 10.1% to 42.3%. CONCLUSION: Average lesion diameter and localization accuracy are highly significant variables for the resected specimen volume. Localization accuracy as a subjective controllable variable is one of the important factors that determine the volume of lesion resection. Single clustered distribution was more susceptible localization accuracy than other characteristic distributions. Improving localization accuracy can reduce resected specimen volume, which can reduce breast defect to a certain extent. Show more

Keywords: Generalized linear model, stereotactic wire localization biopsy, non-palpable breast lesions, breast cancer, microcalcifications

DOI: 10.3233/XST-180462

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 493-502, 2019

Authors: Li, Xinbin | Chen, Zhiqiang | Zhang, Li | Zhu, Xiaohua | Wang, Shengping | Peng, Weijun

Article Type: Research Article

Abstract: BACKGROUND: Grating-based X-ray phase-contrast imaging (GPCI) has received growing interests in recent years due to its high capability of visualizing soft tissue. Breast imaging is one of the most promising candidates for the first clinical application of this imaging modality. OBJECTIVE: In this work, quantitative breast tissue characterization based on GPCI computed tomography (CT) is investigated with a laboratory X-ray tube through a comparison between attenuation-based CT images and phase-contrast CT images. METHODS: The Hounsfield units (HU) scale was introduced to phase-contrast images due to its wide application in clinical medicine. In this work, instead of …water, plastic cylinders composed of polyethylene terephthalate (PET) was treated as the calibration material. An alternative test-retest reliability (TRR) was presented to evaluate the repeatability of GPCI. Comparison between attenuation-based CT imaging and GPCI CT imaging was operated with the use of statistical analysis methods like histograms and receiver operating characteristic (ROC) curves. RESULTS: The determined mean TRR related to cylinders is slightly larger in phase-contrast imaging (0.93) than that in attenuation-based imaging (0.89). With respect to distinguishing breast tissues, the AUC (area under curve) values of ROC curves of phase-contrast images are higher than that of attenuation-based images. CONCLUSIONS: An ex vivo study of GPCI shows that it is a stable imaging modality for visualizing the breast tissue with good repeatability, and that it could be of potential for the diagnosis of breast cancer as well. Show more

Keywords: Breast imaging, phase-contrast tomography, Hounsfield units

DOI: 10.3233/XST-180453

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 503-516, 2019

Authors: Lin, Chia-Hung | Kan, Chung-Dann | Chen, Wei-Ling | Huang, Ping-Tzan

Article Type: Research Article

Abstract: Pleural effusion is a pathologic symptom in which there is accumulation of body fluids around the lungs. A chest radiograph is a rapid examination technique and does not require complex setup for making a preliminary diagnosis of lung and heart diseases. In radiographic visualization, the symptom patterns appear as light or dark areas in the lung cavity. Computer-aided diagnosis is an automatic manner that can rapidly highlight the object region by preanalyzing medical images. It can improve the problems of manual inspection and allow diagnosis in remote medical facilities. Based on the ratios of lung anatomy, the automatic screening manner …based on pattern recognition can be viewed as pixel value detection in the bilateral lung cavities. In this study, a fractional-order convolution (FOC) process is used to enhance the original image for an accurate extrapolation of the desired object in an image. The specific object image feature can be improved, and an accurate quantification of the pleural effusion region can be obtained using the suitable ranges of fractional-order parameters. Based on the boundaries of homogeneous regions, the pixel ratios of the lung anatomy between normal and abnormal conditions can be computed. The pleural effusion sizes and volumes can be rapidly estimated through the number of pixel changes. The experimental results reveal that the feature maps are similar and stable on image enhancement and segmentation with two fractional-order enhancement masks, as fractional-order v  = 0.05 to 0.20 for mask 1# and v  = 0.80 to 0.95 for mask 2#, respectively. The results also demonstrate the feasibility of the study on combining two-dimensional image FOC-process and bounding box pixel analysis to estimate the moderate and large effusion sizes from 500–2,000 mL. Show more

Keywords: Pleural effusion, computer aided diagnosis, fractional-order convolution, fractional-order parameter

DOI: 10.3233/XST-180473

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 517-535, 2019

Authors: Deng, Xiaojuan | Zhao, Yunsong | Li, Hongwei

Article Type: Research Article

Abstract: Reducing radiation dose while maintaining the quality of the reconstructed images is a major challenge in the computed tomography (CT) community. In light of the non-stationary Gaussian noise distribution, we developed a model that incorporates a noise-level weighted total variation (NWTV) regularization term for denoising the projection data. Contrary to the well-known edge-weighted total variation method, which aims for better edge preserving, the proposed NWTV tries to adapt the regularization with the spatially varying noise levels. Experiments on simulated data as well as the real imaging data suggest that the proposed NWTV regularization could achieve quite competitive results. For sinograms …with sharp edges, the NWTV could do a better job at balancing noise reduction and edge preserving, such that noise is removed in a more uniform manner. Another conclusion from our experiments is that the well-recognized stair-casing artifacts of TV regularization play little role in the reconstructed images when the NWTV method is applied to low-dose CT imaging data. Show more

Keywords: Denoising, weighted total variation, low-dose ct, non-stationary gaussian noise

DOI: 10.3233/XST-180469

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 537-557, 2019

Authors: Gou, Junnian | Wu, Xiaoyuan | Dong, Haiying

Article Type: Research Article

Abstract: BACKGROUND: For sparse and limited angle projection Computed Tomography (CT), the reconstructed image usually suffers from considerable artifacts due to undersampled data. OBJECTIVE: To improve image reconstruction quality of sparse and limited angle projection CT, this study tested a novel reconstruction algorithm based on Dictionary Learning (DL) from sparse and limited projections. METHODS: The study used signal sparse representation and feature extraction to render the DL technology, which is constrained by L2 and Lp norms, respectively. A Lp Norm Dictionary Learning term is suitable for regular term of objective function for CT image reconstruction. This is …helpful for solving the objective function by combining algorithm of ART. Based on these features, the new algorithm of ART-DL-Lp is proposed for CT image reconstruction. The alternate solving strategy of the algorithm of “ART first, then adaptive DL” is provided in sequence. The impact on reconstruction results of ART-DL-Lp at different p values (0 < p  < 1) is also considered. RESULTS: For non-ideal projections with noise, the digital experiments show that ART-DL-Lp data were superior to those of ART, SART, and ART-DL-L2. Accordingly, the objective evaluation metrics for non-ideal situation of RMSE, MAE, PSNR, Residuals and SSIM are all better than those of contrasted three algorithms. The metrics curves of ART-DL-Lp algorithm are recorded as the best. In both incomplete projection situations, smaller p -value of ART-DL-Lp algorithm induces more close reconstructed images to the original form and better five objective evaluation metrics. CONCLUSIONS: Overall, the reconstruction efficiency of the proposed ART-DL-Lp for CT imaging using the noisy incomplete projections outperforms ART, SART and ART-DL-L2 algorithms. For ART-DL-Lp algorithm, lower p -values result in better reconstruction performance. Show more

Keywords: CT image reconstruction, incomplete projection, Lp dictionary learning, regular optimization

DOI: 10.3233/XST-180470

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 559-572, 2019

Authors: Zhao, Xianyu | Jiang, Changhui | Zhang, Qiyang | Ge, Yongshuai | Liang, Dong | Liu, Xin | Yang, Yongfeng | Zheng, Hairong | Hu, Zhanli

Article Type: Research Article

Abstract:  Recently, low-dose computed tomography (CT) has become highly desirable due to the increasing attention paid to the potential risks of excessive radiation of the regular dose CT. However, ensuring image quality while reducing the radiation dose in the low-dose CT imaging is a major challenge. Compared to classical filtered back-projection (FBP) algorithms, statistical iterative reconstruction (SIR) methods for modeling measurement statistics and imaging geometry can significantly reduce the radiation dose, while maintaining the image quality in a variety of CT applications. To facilitate low-dose CT imaging, we in this study proposed an improved statistical iterative reconstruction scheme based on the …penalized weighted least squares (PWLS) standard combined with total variation (TV) minimization and sparse dictionary learning (DL), which is named as a method of PWLS-TV-DL. To evaluate this PWLS-TV-DL method, we performed experiments on digital phantoms and physical phantoms, and analyzed the results in terms of image quality and calculation. The results show that the proposed method is better than the comparison methods, which indicates the potential of applying this PWLS-TV-DL method to reconstruct low-dose CT images. Show more

Keywords: Low dose computed tomography, penalized weighted least squares, total variation, dictionary learning

DOI: 10.3233/XST-180477

Citation: Journal of X-Ray Science and Technology, vol. 27, no. 3, pp. 573-590, 2019