DEBISim: A simulation pipeline for dual energy CT-based baggage inspection systems1
CONCLUSION: DEBISim is an end-to-end simulation framework for rapidly generating X-ray baggage data for dual energy cone-beam scanners.PMID:33646192 | DOI:10.3233/XST-200808 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - March 1, 2021 Category: Radiology Authors: Ankit Manerikar Fangda Li Avinash C Kak Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

A feasibility study of realizing low-dose abdominal CT using deep learning image reconstruction algorithm
J Xray Sci Technol. 2021 Feb 18. doi: 10.3233/XST-200826. Online ahead of print.ABSTRACTOBJECTIVES: To explore the feasibility of achieving diagnostic images in low-dose abdominal CT using a Deep Learning Image Reconstruction (DLIR) algorithm.METHODS: Prospectively enrolled 47 patients requiring contrast-enhanced abdominal CT scans. The late-arterial phase scan was added and acquired using lower-dose mode (tube current range, 175-545 mA; 80 kVp for patients with BMI ≤24 kg/m2 and 100 kVp for patients with BMI> 24 kg/m2) and reconstructed with DLIR at medium setting (DLIR-M) and high setting (DLIR-H), ASIR-V at 0% (FB...
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Lu-Lu Li Huang Wang Jian Song Jin Shang Xiao-Ying Zhao Bin Liu Source Type: research

Screening of COVID-19 based on the extracted radiomics features from chest CT images
CONCLUSION: This study demonstrates that the ML model based on RFE+KNN classifier achieves the highest performance to differentiate patients with a confirmed infection caused by COVID-19 from the suspected cases.PMID:33612539 | DOI:10.3233/XST-200831 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 22, 2021 Category: Radiology Authors: Seyed Masoud Rezaeijo Razzagh Abedi-Firouzjah Mohammadreza Ghorvei Samad Sarnameh Source Type: research

Optically transparent glass modified with metal oxides for X-rays and gamma rays shielding material
CONCLUSIONS: Our findings indicate that the proposed novel glass samples have good shielding properties and optical characteristics, which can pave the way for their utilization as transparent radiation-shielding materials in medical and industrial applications.PMID:33579888 | DOI:10.3233/XST-200780 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 13, 2021 Category: Radiology Authors: Khalid I Hussein Mohammed S Alqahtani Iwona Grelowska Manuela Reben Hesham Afif Heba Zahran I S Yaha El Sayed Yousef Source Type: research

Development of a novel computational method using computed tomography images for the early detection and severity classification of COVID-19 cases
CONCLUSION: The study results indicate the possibility of relying on the proposed methodology for discovering the effects of the SARS-CoV-2 virus in the lungs through CT imaging analysis with limited dependency on radiologists.PMID:33579889 | DOI:10.3233/XST-200794 (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 13, 2021 Category: Radiology Authors: M A Abbas M S Alqahtani A J Alkulib H M Almohiy R F Alshehri E A Alamri A A Alamri Source Type: research

Quality improvement of general anteroposterior radiographic image of vertebral body according to optimum angle of incidence.
CONCLUSION: When you apply the optimum angle of incidence, the distortion of image was minimized and an image between the joints adjacent to the anteroposterior vertebral image with an accurate structure was obtained. As a result, we were able to improve the quality of the image and enhance diagnostic information. PMID: 33554934 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 9, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Impact of respiratory motion artifact on coronary image quality of one beat coronary CT angiography.
Authors: Shen W, Chen Y, Qian W, Liu W, Zhu Y, Xu Y, Zhu X Abstract BACKGROUND: Accuracy of CT-derived fractional flow reserve depends on good image quality. Thus, improving image quality during coronary CT angiography (CCTA) is important. OBJECTIVE: To investigate impact of respiratory motion artifact on coronary image quality focusing on vessel diameter and territory during one beat CCTA by a 256-row detector. METHODS: We retrospectively reviewed patients who underwent CCTA under free-breathing (n = 100) and breath-holding (n = 100), respectively. Coronary image quality is defined as 4-1 from exce...
Source: Journal of X-Ray Science and Technology - February 9, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

X- ray absorption parameters studies of P2O5- SnCl2-SnO bioactive glass system.
Authors: Alhuthali AMS, Kumar A, Sayyed MI, Al-Hadeethi Y Abstract The main objective of this work is to explore the X-ray interaction properties of P2O5- SnCl2-SnO bioactive glass system using Photon Shielding and Dosimetry (Phys-X/PSD) software in the energy range 10-150 keV. The study of these parameters will have applications in various fields of nuclear medicine, medical technology, and other medical applications. The value of mass attenuation coefficients (μm) and effective atomic numbers (Zeff) decrease whereas the value of mean free path as well as half value layer increases with rises in energy in the...
Source: Journal of X-Ray Science and Technology - February 9, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Predictive role of T2WI and ADC-derived texture parameters in differentiating Gleason score 3  + 4 and 4 + 3 prostate cancer.
CONCLUSIONS: The study demonstrates that using T2WI and ADC-derived image texture parameters has a potentially predictive role in differentiating GS 3 + 4 and GS 4 + 3 PCa. PMID: 33522997 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - February 2, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Computer aid screening of COVID-19 using X-ray and CT scan images: An inner comparison.
In conclusion, the findings of this analysis study are beneficial for the researchers who are working towards designing computer aid tools for screening COVID-19 infection diseases. PMID: 33492267 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - January 27, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Calculation of effective atomic numbers using a rational polynomial approximation method with a dual-energy X-ray imaging system.
Authors: Chang CH, Ni YC, Tseng SP Abstract The study aims to develop a rational polynomial approximation method for improving the accuracy of the effective atomic number calculation with a dual-energy X-ray imaging system. This method is based on a multi-materials calibration model with iterative optimization, which can improve the calculation accuracy of the effective atomic number by adding a rational term without increasing the computation time. The performance of the proposed rational polynomial approximation method is demonstrated and validated by both simulated and experimental studies. The twelve reference ...
Source: Journal of X-Ray Science and Technology - January 27, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Coronary microvascular dysfunction: An important interpretation on the clinical significance of transient ischemic dilation of the left ventricle on myocardial perfusion imaging.
Authors: Chen L, Zhang M, Jiang J, Lei B, Sun X Abstract PURPOSE: To further investigate the clinical significance of transient ischemic dilation (TID) on myocardial perfusion imaging (MPI) by analyzing the effect of anisodamine hydrobromide (a drug that can effectively ameliorate microcirculation) on the patients with isolated TID and the findings of previous literatures. METHODS: Total 107 patients with isolated TID (TID value≥1.11) were randomly divided into group A (n = 36; intravenous administration of anisodamine hydrobromide), group N (n = 36; intravenous administration of isosorbide dinitrate...
Source: Journal of X-Ray Science and Technology - January 27, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

COVID-19 diagnosis from chest X-ray images using transfer learning: Enhanced performance by debiasing dataloader.
CONCLUSION: This study demonstrated that the proposed CNN model called nCoV-NET can be utilized for reliably detecting COVID-19 cases using chest X-ray images to accelerate the triaging and save critical time for disease control as well as assisting the radiologist to validate their initial diagnosis. PMID: 33459685 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - January 20, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Dual residual convolutional neural network (DRCNN) for low-dose CT imaging.
Authors: Feng Z, Cai A, Wang Y, Li L, Tong L, Yan B Abstract The excessive radiation doses in the application of computed tomography (CT) technology pose a threat to the health of patients. However, applying a low radiation dose in CT can result in severe artifacts and noise in the captured images, thus affecting the diagnosis. Therefore, in this study, we investigate a dual residual convolution neural network (DRCNN) for low-dose CT (LDCT) imaging, whereby the CT images are reconstructed directly from the sinogram by integrating analytical domain transformations, thus reducing the loss of projection information. W...
Source: Journal of X-Ray Science and Technology - January 20, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

A metal artifact reduction scheme in CT by a Poisson fusion sinogram based postprocessing method.
CONCLUSIONS: This study demonstrated that with the same prior image, applying the proposed Poisson FS-MAR method can achieve the higher image quality than using the interpolation-based algorithm. PMID: 33459687 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - January 20, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Iatrogenic ureteral injury during retroperitoneal laparoscopy for large renal cysts: What we learned and a review of the literature.
CONCLUSIONS: For single large (diameter >  70 mm) renal cysts located at the lower pole of the kidney, it is recommended to not completely dissect out and mobilize the entire renal cyst for cyst decortication in order to avoid injuring the ureter. Iatrogenic ureteral injury increases the risk of readmission and serious life-threatening complications. The immediate diagnosis and proper management ureteric injury can reduce complications and long term sequalae. PMID: 33459688 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - January 20, 2021 Category: Radiology Tags: J Xray Sci Technol Source Type: research

A pilot study of radiomics signature based on biparametric MRI for preoperative prediction of extrathyroidal extension in papillary thyroid carcinoma.
CONCLUSIONS: Radiomics features based on pre-contrast T2WI and T2WI-FS is helpful to predict aggressive ETE in PTC. Particularly, the model trained using the optimally selected T2WI-FS image features yields the best classification performance. The most important features relate to lesion size and the texture heterogeneity of the tumor region. PMID: 33325448 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - December 18, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Compton-camera-based SPECT for thyroid cancer imaging.
Authors: Yu H, Wang G Abstract Thyroid cancer is the most common type of endocrine-related cancer and the most common cancer in young women. Currently, single photon emission computed tomography (SPECT) and computed tomography (CT) are used with radioiodine scintigraphy to evaluate patients with thyroid cancer. The gamma camera for SPECT contains a mechanical collimator that greatly compromises dose efficiency and limits diagnostic sensitivity. Fortunately, the Compton camera is emerging as an ideal approach for mapping the distribution of radiopharmaceuticals inside the thyroid. In this preliminary study, based on...
Source: Journal of X-Ray Science and Technology - December 18, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Hybrid diffusion tensor imaging feature-based AD classification.
CONCLUSIONS: This study demonstrates that the new method and models not only improve the accuracy of detecting AD, but also avoid bias caused by the method of direct dimensionality reduction from high dimensional data. PMID: 33325450 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - December 18, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Accelerated strategy for the MLEM algorithm.
CONCLUSIONS: The proposed new computational method involving the relaxation strategy has a faster convergence speed than the original method. PMID: 33252106 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - December 1, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Development of X-ray phase CT with a hybrid configuration of Lau and Talbot-Lau interferometers.
Authors: Kageyama M, Okajima K, Maesawa M, Nonoguchi M, Nonoguchi M, Kuribayashi M, Hara Y, Momose A Abstract X-ray phase computed tomography (CT) is used to observe the inside of light materials. In this paper, we report a new study to develop and test a laboratory assembled X-ray phase CT system that comprises an X-ray Lau interferometer, a rotating Mo anode X-ray tube, and a detector with high spatial resolution. The system has a high spatial resolution lower than 10μm, which is evaluated by differentiating neighbouring carbon fibres in a polymer composite material. The density resolution is approximately 0.0...
Source: Journal of X-Ray Science and Technology - November 11, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Using artificial intelligence to assist radiologists in distinguishing COVID-19 from other pulmonary infections.
CONCLUSION: A deep learning algorithm-based AI model developed in this study successfully improved radiologists' performance in distinguishing COVID-19 from other pulmonary infections using chest CT images. PMID: 33164982 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - November 11, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Comparison of image quality and radiation dose using different pre-ASiR-V and post-ASiR-V levels in coronary computed tomography angiography.
Authors: Zhao Y, Li D, Liu Z, Geng X, Zhang T, Xu Y Abstract OBJECTIVE: To determine the optimal pre-adaptive and post-adaptive level statistical iterative reconstruction V (ASiR-V) for improving image quality and reducing radiation dose in coronary computed tomography angiography (CCTA). METHODS: The study was divided into two parts. In part I, 150 patients for CCTA were prospectively enrolled and randomly divided into 5 groups (A, B, C, D, and E) with progressive scanning from 40% to 80% pre-ASiR-V with 10% intervals and reconstructing with 70% post-ASiR-V. The signal-to-noise ratio (SNR) and contrast-to-nois...
Source: Journal of X-Ray Science and Technology - November 11, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Automated location of thyroid nodules in ultrasound images with improved YOLOV3 network.
This study proposes an automatic detection algorithm to locate nodules in B ultrasound images and Doppler ultrasound images. This method can be used to screen thyroid nodules and provide a basis for subsequent automatic segmentation and intelligent diagnosis. METHODS: We develop and optimize an improved YOLOV3 model for detecting thyroid nodules in ultrasound images with B-mode and Doppler mode. Improvements include (1) using the high-resolution network (HRNet) as the basic network for gradually extracting high-level semantic features to reduce the missed detection and misdetection, (2) optimizing the loss function for...
Source: Journal of X-Ray Science and Technology - November 4, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

An effective sinogram inpainting for complementary limited-angle dual-energy computed tomography imaging using generative adversarial networks.
In conclusion, both qualitative and quantitative comparison and analysis demonstrate that our proposed method achieves a good artifact suppression effect and can suitably solve the complementary limited-angle problem. PMID: 33104055 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - October 28, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Applying a radiomics-based strategy to preoperatively predict lymph node metastasis in the resectable pancreatic ductal adenocarcinoma.
Authors: Liu P, Gu Q, Hu X, Tan X, Liu J, Xie A, Huang F Abstract PURPOSE: This retrospective study is designed to develop a Radiomics-based strategy for preoperatively predicting lymph node (LN) status in the resectable pancreatic ductal adenocarcinoma (PDAC) patients. METHODS: Eighty-five patients with histopathological confirmed PDAC are included, of which 35 are LN metastasis positive and 50 are LN metastasis negative. Initially, 1,124 radiomics features are computed from CT images of each patient. After a series of feature selection, a Radiomics logistic regression (LOG) model is developed. Subsequently, t...
Source: Journal of X-Ray Science and Technology - October 22, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Material decomposition for simulated dual-energy breast computed tomography via hybrid optimization method.
CONCLUSIONS: This study demonstrates the potential of applying dual-energy reconstruction in breast CT to detect and separate clustered MCs from healthy breast tissues without noise amplification. Compared to other competing methods, the proposed algorithm achieves the best noise suppression performance for both reconstructed and decomposed images. PMID: 33044222 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - October 14, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Low-dose CT reconstruction method based on prior information of normal-dose image.
CONCLUSIONS: This study presents a new low-dose CT reconstruction method based on prior information of normal-dose image (PI-NDI) for sparse-view CT image reconstruction. The experimental results validate that the new method has superior performance over other state-of-art methods. PMID: 33044223 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - October 14, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Predicting fringe visibility in dual-phase grating interferometry with polychromatic x-ray sources.
Authors: Yan A, Wu X, Liu H Abstract Dual phase grating X-ray interferometry is radiation dose-efficient as compared to common Talbot-Lau grating interferometry. The authors developed a general quantitative theory to predict the fringe visibility in dual-phase grating x-ray interferometry with polychromatic x-ray sources. The derived formulas are applicable to setups with phase gratings of any phase modulation and with either monochromatic or polychromatic x-rays. Numerical simulations are presented to validate the derived formulas. The theory provides useful tools for design optimization of dual-phase grating x-ra...
Source: Journal of X-Ray Science and Technology - October 14, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Development of a computational tool for estimating computed tomography dose parameters.
CONCLUSIONS: The prototyped computational model provides a tool for the simulation of a machine-specific spectrum and CT dose parameters using a single dose measurement. PMID: 32986646 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - September 29, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Automatic tooth roots segmentation of cone beam computed tomography image sequences using U-net and RNN.
CONCLUSIONS: The study demonstrates that the new method combining attention U-net with RNN yields the promising results of automatic tooth roots segmentation, which has potential to help improve the segmentation efficiency and accuracy in future clinical practice. PMID: 32986647 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - September 29, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Evaluation of reconstruction algorithms for  a stationary digital breast tomosynthesis system using a carbon nanotube X-ray source array.
Evaluation of reconstruction algorithms for a stationary digital breast tomosynthesis system using a carbon nanotube X-ray source array. J Xray Sci Technol. 2020 Sep 10;: Authors: Hu Z, Chen Z, Zhou C, Hong X, Chen J, Zhang Q, Jiang C, Ge Y, Yang Y, Liu X, Zheng H, Li Z, Liang D Abstract Breast cancer is the most frequently diagnosed cancer in women worldwide. Digital breast tomosynthesis (DBT), which is based on limited-angle tomography, was developed to solve tissue overlapping problems associated with traditional breast mammography. However, due to the problems associated with tube movement dur...
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Diagnostic performance on multiple parameters of real-time ultrasound shear wave elastography for evaluating nonalcoholic fatty liver disease: A rabbit model.
CONCLUSIONS: Real-time US-SWE is an accurate, noninvasive technique for evaluating the histological stages of NAFLD by measuring liver stiffness. We recommend using the mean elastic modulus to differentiate the histological stages, with the minimum and maximum elastic modulus as valuable complements. PMID: 32925160 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Quick and accurate selection of hand images among radiographs from various body parts using deep learning.
CONCLUSIONS: Deep learning showed promise to enable efficiently automatic selection of target X-ray images of RA patients. PMID: 32925161 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Application of texture analysis based on T2-weighted magnetic resonance images in discriminating Gleason scores of prostate cancer.
Authors: Pan R, Yang X, Shu Z, Gu Y, Weng L, Jia Y, Feng J Abstract OBJECTIVE: To investigate the value of texture analysis in magnetic resonance images for the evaluation of Gleason scores (GS) of prostate cancer. METHODS: Sixty-six prostate cancer patients are retrospective enrolled, which are divided into five groups namely, GS = 6, 3 + 4, 4 + 3, 8 and 9-10 according to postoperative pathological results. Extraction and analysis of texture features in T2-weighted MR imaging defined tumor region based on pathological specimen after operation are performed by texture software OmniKinetics. The valu...
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Deformable registration and region-of-interest image reconstruction in  sparse repeat CT scanning.
CONCLUSION: Our method is considerably faster than existing methods, thereby enabling intraoperative online repeat scanning that it is accurate and accounts for position, deformation, and structure changes at a fraction of the radiation dose required by existing methods. PMID: 32925163 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Fully-automatic segmentation of coronary artery using growing algorithm.
In this study, we propose and test a fully automatic coronary artery segmentation method that does not require any human-computer interaction. The proposed method uses a growing strategy and contains three main parts namely, (1) the initial seed detection that automatically detects the root points of the left and right coronary arteries where the ascending aorta meets the coronary arteries, (2) the growing strategy that searches for the neighborhood blocks to decide the existence of coronary arteries with an improved convolutional neural network, and (3) the iterative termination condition that decides whether the growing ...
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Evaluation of dynamic lung changes during coronavirus disease 2019 (COVID-19) by quantitative computed tomography.
This study aims to trace the dynamic lung changes of coronavirus disease 2019 (COVID-19) using computed tomography (CT) images by a quantitative method. METHODS: In this retrospective study, 28 confirmed COVID-19 cases with 145 CT scans are collected. The lesions are detected automatically and the parameters including lesion volume (LeV/mL), lesion percentage to lung volume (LeV%), mean lesion density (MLeD/HU), low attenuation area lower than - 400HU (LAA-400%), and lesion weight (LM/mL*HU) are computed for quantification. The dynamic changes of lungs are traced from the day of initial symptoms to the day of discharge...
Source: Journal of X-Ray Science and Technology - September 16, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

Retrospective 3D analysis of bone regeneration after cystectomy of odontogenic cysts.
CONCLUSIONS: By establishing a standardized 3D method for evaluating bone regeneration, healing can be better monitored and evaluated. PMID: 32804111 [PubMed - as supplied by publisher] (Source: Journal of X-Ray Science and Technology)
Source: Journal of X-Ray Science and Technology - August 19, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research

A retrospective study of the initial chest CT imaging findings in 50 COVID-19 patients stratified by gender and age.
Authors: Gu Q, Ouyang X, Xie A, Tan X, Liu J, Huang F, Liu P Abstract OBJECTIVE: To retrospectively analyze and stratify the initial clinical features and CT imaging findings of patients with COVID-19 by gender and age. METHODS: Data of 50 COVID-19 patients were collected in two hospitals. The clinical manifestations, laboratory examination and chest CT imaging features were analyzed, and a stratification analysis was performed according to gender and age [younger group:
Source: Journal of X-Ray Science and Technology - August 19, 2020 Category: Radiology Tags: J Xray Sci Technol Source Type: research