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Peri-lesion regions in differentiating suspicious breast calcification-only lesions specifically on contrast enhanced mammography J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-29 Kun Cao, Fei Gao, Rong Long, Fan-Dong Zhang, Chen-Cui Huang, Min Cao, Yi-Zhou Yu, Ying-Shi Sun
PURPOSE: The explore the added value of peri-calcification regions on contrast-enhanced mammography (CEM) in the differential diagnosis of breast lesions presenting as only calcification on routine mammogram. METHODS: Patients who underwent CEM because of suspicious calcification-only lesions wereincluded. The test set included patients between March 2017 and March 2019, while the validation set was
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Multimodal feature fusion in deep learning for comprehensive dental condition classification J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-12 Shang-Ting Hsieh, Ya-Ai Cheng
BACKGROUND: Dental health issues are on the rise, necessitating prompt and precise diagnosis. Automated dental condition classification can support this need. OBJECTIVE: The study aims to evaluate the effectiveness of deep learning methods and multimodal feature fusion techniques in advancing the field of automated dental condition classification. METHODS AND MATERIALS: A dataset of 11,653 clinically
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Comparative study of abdominal CT enhancement in overweight and obese patients based on different scanning modes combined with different contrast medium concentrations J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-12 Kai Gao, Ze-Peng Ma, Tian-Le Zhang, Yi-Wen Liu, Yong-Xia Zhao
PURPOSE: To compare image quality, iodine intake, and radiation dose in overweight and obese patients undergoing abdominal computed tomography (CT) enhancement using different scanning modes and contrast medium. METHODS: Ninety overweight and obese patients (25 kg/m2≤body mass index (BMI)< 30 kg/m2 and BMI≥30 kg/m2) who underwent abdominal CT-enhanced examinations were randomized into three groups
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Dosimetry and treatment efficiency of SBRT using TaiChiB radiotherapy system for two-lung lesions with one overlapping organs at risk J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-12 Yanhua Duan, Aihui Feng, Hao Wang, Hua Chen, Hengle Gu, Yan Shao, Ying Huang, Zhenjiong Shen, Qing Kong, Zhiyong Xu
Purpose:This study aims to assess the dosimetry and treatment efficiency of TaiChiB-based Stereotactic Body Radiotherapy (SBRT) plans applying to treat two-lung lesions with one overlapping organs at risk. Methods:For four retrospective patients diagnosed with two-lung lesions each patient, four treatment plans were designed including Plan Edge, TaiChiB linac-based, RGS-based, and a linac-RGS hybrid
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Photothermal effect in X-ray images for computed tomography of metallic parts: Stainless steel spheres J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-09 Verena M. Moock, Darien E. Arce Chávez, Crescencio García-Segundo, Leopoldo Ruiz-Huerta
Abstract BACKGROUND: The environmental impact on industrial X-ray tomography systems has gained its attention in terms of image precision and metrology over recent years, yet is still complex due to the variety of applications. OBJECTIVE: The current study explores the photothermal repercussions of the overall radiation exposure time. It shows the emerging dimensional uncertainty when measuring a stainless
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Semi-supervised segmentation of metal-artifact contaminated industrial CT images using improved CycleGAN J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-06 Shi Bo Jiang, Yue Wen Sun, Shuo Xu, Hua Xia Zhang, Zhi Fang Wu
Accurate segmentation of industrial CT images is of great significance in industrial fields such as quality inspection and defect analysis. However, reconstruction of industrial CT images often suffers from typical metal artifacts caused by factors like beam hardening, scattering, statistical noise, and partial volume effects. Traditional segmentation methods are difficult to achieve precise segmentation
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Multi-parametric assessment of cardiac magnetic resonance images to distinguish myocardial infarctions: A tensor-based radiomics feature J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-06 Dehua Wang, Hayder Jasim Taher, Murtadha Al-Fatlawi, Badr Ahmed Abdullah, Munojat Khayatovna Ismailova, Razzagh Abedi-Firouzjah
AIM:This study assessed the myocardial infarction (MI) using a novel fusion approach (multi-flavored or tensor-based) of multi-parametric cardiac magnetic resonance imaging (CMRI) at four sequences; T1-weighted (T1W) in the axial plane, sense-balanced turbo field echo (sBTFE) in the axial plane, late gadolinium enhancement of heart short axis (LGE-SA) in the sagittal plane, and four-chamber views of
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An adaptive weighted ensemble learning network for diabetic retinopathy classification J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-06 Panpan Wu, Yue Qu, Ziping Zhao, Yue Cui, Yurou Xu, Peng An, Hengyong Yu
Diabetic retinopathy (DR) is one of the leading causes of blindness. However, because the data distribution of classes is not always balanced, it is challenging for automated early DR detection using deep learning techniques. In this paper, we propose an adaptive weighted ensemble learning method for DR detection based on optical coherence tomography (OCT) images. Specifically, we develop an ensemble
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Deep-silicon photon-counting x-ray projection denoising through reinforcement learning J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-06 Md Sayed Tanveer, Christopher Wiedeman, Mengzhou Li, Yongyi Shi, Bruno De Man, Jonathan S. Maltz, Ge Wang
BACKGROUND:In recent years, deep reinforcement learning (RL) has been applied to various medical tasks and produced encouraging results. OBJECTIVE:In this paper, we demonstrate the feasibility of deep RL for denoising simulated deep-silicon photon-counting CT (PCCT) data in both full and interior scan modes. PCCT offers higher spatial and spectral resolution than conventional CT, requiring advanced
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The investigation of dose rate and photon beam energy dependence of optimized PASSAG polymer gel dosimeter using magnetic resonance imaging J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-06 Bo Liu, Shaima Haithem Zaki, Eduardo García, Amanda Bonilla, Daha Thabit, Aya Hussein Adab
OBJECTIVE:It seems that dose rate (DR) and photon beam energy (PBE) may influence the sensitivity and response of polymer gel dosimeters. In the current project, the sensitivity and response dependence of optimized PASSAG gel dosimeter (OPGD) on DR and PBE were assessed. MATERIALS AND METHODS:We fabricated the OPGD and the gel samples were irradiated with various DRs and PBEs. Then, the sensitivity
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Application of dose-gradient function in reducing radiation induced lung injury in breast cancer radiotherapy J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Han Bai, Hui Song, Qianyan Li, Jie Bai, Ru Wang, Xuhong Liu, Feihu Chen, Xiang Pan
OBJECTIVE:Try to create a dose gradient function (DGF) and test its effectiveness in reducing radiation induced lung injury in breast cancer radiotherapy. MATERIALS AND METHODS:Radiotherapy plans of 30 patients after breast-conserving surgery were included in the study. The dose gradient function was defined as DGH=VDVp3 , then the area under the DGF curve of each plan was calculated in rectangular
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Diagnosis of Covid-19 from CT slices using Whale Optimization Algorithm, Support Vector Machine and Multi-Layer Perceptron J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 R. Betshrine Rachel, H. Khanna Nehemiah, Vaibhav Kumar Singh, Rebecca Mercy Victoria Manoharan
BACKGROUND:The coronavirus disease 2019 is a serious and highly contagious disease caused by infection with a newly discovered virus, named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). OBJECTIVE:A Computer Aided Diagnosis (CAD) system to assist physicians to diagnose Covid-19 fromchest Computed Tomography (CT) slices is modelled and experimented. METHODS:The lung tissues are segmented
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Artificial intelligence auxiliary diagnosis and treatment system for breast cancer in developing countries J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Wenxiu Li, Fangfang Gou, Jia Wu
BACKGROUND:In many developing countries, a significant number of breast cancer patients are unable to receive timely treatment due to a large population base, high patient numbers, and limited medical resources. OBJECTIVE:This paper proposes a breast cancer assisted diagnosis system based on electronic medical records. The goal of this system is to address the limitations of existing systems, which
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A fast response time gas ionization chamber detector with a grid structure J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Jiahao Chang, Chaoyang Zhu, Yuanpeng Song, Zhentao Wang
The time response characteristic of the detector is crucial in radiation imaging systems. Unfortunately, existing parallel plate ionization chamber detectors have a slow response time, which leads to blurry radiation images. To enhance imaging quality, the electrode structure of the detector must be modified to reduce the response time. This paper proposes a gas detector with a grid structure that
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The mechanism of moire artifacts in single-grating imaging systems and image quality optimization J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Fangke Zong, Jun Yang, Jun Jiang, JinChuan Guo
In the X-ray single-grating imaging system, the acquisition of frequency information is the key step of phase-contrast and scattering information recovery. In the process of information extraction, it is easy to lead to the degradation of imaging quality due to the Moire Artifact, thus limiting thedevelopment and application of X-ray single-grating imaging system. In order to address the above problems
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Decomposition iteration strategy for low-dose CT denoising J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Zhiyuan Li, Yi Liu, Pengcheng Zhang, Jing Lu, Zhiguo Gui
In the medical field, computed tomography (CT) is a commonly used examination method, but the radiation generated increases the risk of illness in patients. Therefore, low-dose scanning schemes have attracted attention, in which noise reduction is essential. We propose a purposeful and interpretable decomposition iterative network (DISN) for low-dose CT denoising. This method aims to make the network
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Nomograms combining computed tomography-based body composition changes with clinical prognostic factors to predict survival in locally advanced cervical cancer patients J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Baoyue Fu, Longyu Wei, Chuanbin Wang, Baizhu Xiong, Juan Bo, Xueyan Jiang, Yu Zhang, Haodong Jia, Jiangning Dong
OBJECTIVE:To explore the value of body composition changes (BCC) measured by quantitative computed tomography (QCT) for evaluating the survival of patients with locally advanced cervical cancer (LACC) underwent concurrent chemoradiotherapy (CCRT), nomograms combined BCC with clinical prognostic factors (CPF) were constructed to predict overall survival (OS) and progression-free survival (PFS). METHODS:Eighty-eight
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Research on breast cancer pathological image classification method based on wavelet transform and YOLOv8 J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-05 Yunfeng Yang, Jiaqi Wang
Breast cancer is one of the cancers with high morbidity and mortality in the world, which is a serious threat to the health of women. With the development of deep learning, the recognition about computer-aided diagnosis technology is getting higher and higher. And the traditional data feature extraction technology has been gradually replaced by the feature extraction technology based on convolutional
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Reduction of overfitting on the highly imbalanced ISIC-2019 skin dataset using deep learning frameworks J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-12-30 Erapaneni Gayatri, S.L. Aarthy
BACKGROUND:With the rapid growth of Deep Neural Networks (DNN) and Computer-Aided Diagnosis (CAD), more significant works have been analysed for cancer related diseases. Skin cancer is the most hazardous type of cancer that cannot be diagnosed in the early stages. OBJECTIVE:The diagnosis of skin cancer is becoming a challenge to dermatologists as an abnormal lesion looks like an ordinary nevus at the
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Performance evaluation of quantitative material decomposition in slow kVp switching dual-energy CT J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-12-30 Chenchen Ma, Ting Su, Jiongtao Zhu, Xin Zhang, Hairong Zheng, Dong Liang, Na Wang, Yunxin Zhang, Yongshuai Ge
BACKGROUND:Slow kVp switching technique is an important approach to realize dual-energy CT (DECT) imaging, but its performance has not been thoroughly investigated yet. OBJECTIVE:This study aims at comparing and evaluating the DECT imaging performance of different slow kVp switching protocols, andthus helps determining the optimal system settings. METHODS:To investigate the impact of energy separation
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A novel multi-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-03 Yang Kang, Rui Wu, Peizheng Li, Qingpei Li, Sen Wu, Tingting Tan, Yingrui Li, Gangqiang Zha
BACKGROUND: The gangue content in coal seriously affects the calorific value produced by its combustion. In practical applications, gangue in coal needs to be completely separated. The pseudo-dual-energy X-ray method does not have high sorting accuracy. OBJECTIVE: This study aims to propose a novelmulti-dimensional coal and gangue X-ray sorting algorithm based on CdZnTe photon counting detectors to
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Diagnostic reference levels in spinal CT: Jordanian assessments and global benchmarks J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2024-01-03 Mohammad Rawashdeh, Abdel-Baset Bani Yaseen, Mark McEntee, Andrew England, Praveen Kumar, Charbel Saade
BACKGROUND: To reduce radiation dose and subsequent risks, several legislative documents in different countries describe the need for Diagnostic Reference Levels (DRLs). Spinal radiography is a common and high-dose examination. Therefore, the aim of this work was to establish the DRL for Computed Tomography (CT) examinations of the spine in healthcare institutions across Jordan. METHODS: Data was retrieved
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A deep learning and radiomics based Alberta stroke program early CT score method on CTA to evaluate acute ischemic stroke J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-11-17 Ting Fang, Naijia Liu, Shengdong Nie, Shouqiang Jia, Xiaodan Ye
BACKGROUND: Alberta stroke program early CT score (ASPECTS) is a semi-quantitative evaluation method used to evaluate early ischemic changes in patients with acute ischemic stroke, which can guide physicians in treatment decisions and prognostic judgments. OBJECTIVE: We propose a method combining deep learning and radiomics to alleviate the problem of large inter-observer variance in ASPECTS faced
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Multiple energy X-ray imaging of metal oxide particles inside gingival tissues J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-11-10 Jarrod Cortez, Ignacio Romero, Jason Ngo, Md Sayed Tanveer Azam, Chuang Niu, Cássio Luiz Coutinho Almeida-da-Silva, Leticia Ferreira Cabido, David M. Ojcius, Wei-Chun Chin, Ge Wang, Changqing Li
BACKGROUND:Periodontal disease affects over 50% of the global population and is characterized by gingivitis as the initial sign. One dental health issue that may contribute to the development of periodontal disease is foreign body gingivitis (FBG), which can result from exposure to some kinds of foreign metal particles from dental products or food. OBJECTIVE:We design a novel, portable, affordable
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APNet: Adaptive projection network for medical image denoising J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-10-31 Qiyi Song, Xiang Li, Mingbao Zhang, Xiangyi Zhang, Dang N.H. Thanh
BACKGROUND:In clinical medicine, low-dose radiographic image noise reduces the quality of the detected image features and may have a negative impact on disease diagnosis. OBJECTIVE:In this study, Adaptive Projection Network (APNet) is proposed to reduce noise from low-dose medical images. METHODS:APNet is developed based on an architecture of the U-shaped network to capture multi-scale data and achieve
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Fusion extracted features from deep learning for identification of multiple positioning errors in dental panoramic imaging J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-10-09 Hsin-Yueh Su, Shang-Ting Hsieh, Kun-Zhe Tsai, Yu-Li Wang, Chi-Yuan Wang, Shih-Yen Hsu, Kuo-Ying Liu, Yung-Hui Huang, Ya-Wen Wei, Nan-Han Lu, Tai-Been Chen
BACKGROUND:Dental panoramic imaging plays a pivotal role in dentistry for diagnosis and treatment planning. However, correctly positioning patients can be challenging for technicians due to the complexity of the imaging equipment and variations in patient anatomy, leading to positioning errors. These errors can compromise image quality and potentially result in misdiagnoses. OBJECTIVE:This research
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A novel fusion method for X-ray phase contrast imaging based on fast adaptive bidimensional empirical mode decomposition J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-10-09 Zonghan Tian, Siwei Tao, Ling Bai, Yueshu Xu, Xu Liu, Cuifang Kuang
BACKGROUNDS:X-ray phase contrast imaging (XPCI) can separate the attenuation, refraction, and scattering signals of the object. The application of image fusion enables the concentration of distinctive information into a single image. OBJECTIVE:To explore the application value of a novel image fusion method for a XPCI system and a computed tomography (CT) system. METHODS:The means of fast adaptive bidimensional
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Application of radiomics based on chest CT-enhanced dual-phase imaging in the immunotherapy of non-small cell lung cancer J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-10-06 Ze-Peng Ma, Xiao-Lei Li, Kai Gao, Tian-Le Zhang, Heng-Di Wang, Yong-Xia Zhao
OBJECTIVE:To explore the value of applying computed tomography (CT) radiomics based on different CT-enhanced phases to determine the immunotherapeutic efficacy of non-small cell lung cancer (NSCLC). METHODS:106 patients with NSCLC who underwent immunotherapy are randomly divided into training (74)and validation (32) groups. CT-enhanced arterial and venous phase images of patients before treatment are
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A densely connected LDCT image denoising network based on dual-edge extraction and multi-scale attention under compound loss J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-09-19 Lina Jia, Xu He, Aimin Huang, Beibei Jia, Zhiguo Gui
BACKGROUND:Low dose computed tomography (LDCT) uses lower radiation dose, but the reconstructed images contain higher noise that can have negative impact in disease diagnosis. Although deep learning with the edge extraction operators reserves edge information well, only applying the edge extractionoperators to input LDCT images does not yield overall satisfactory results. OBJECTIVE:To improve LDCT
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MTAN: A semi-supervised learning model for kidney tumor segmentation J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-09-14 Peng Sun, Sijing Yang, Haolin Guan, Taiping Mo, Bonan Yu, Zhencheng Chen
BACKGROUND:Medical image segmentation is crucial in disease diagnosis and treatment planning. Deep learning (DL) techniques have shown promise. However, optimizing DL models requires setting numerous parameters, and demands substantial labeled datasets, which are labor-intensive to create. OBJECTIVE:This study proposes a semi-supervised model that can utilize labeled and unlabeled data to accurately
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CGP-Uformer: A low-dose CT image denoising Uformer based on channel graph perception J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-09-12 Huimin Yan, Chenyun Fang, Peng Liu, Zhiwei Qiao
BACKGROUND:An effective method for achieving low-dose CT is to keep the number of projection angles constant while reducing radiation dose at each angle. However, this leads to high-intensity noise in the reconstructed image, adversely affecting subsequent image processing, analysis, and diagnosis.OBJECTIVE:This paper proposes a novel Channel Graph Perception based U-shaped Transformer (CGP-Uformer)
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Analytical reconstructions of full-scan multiple source-translation computed tomography under large field of views J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-09-12 Zhisheng Wang, Yue Liu, Shunli Wang, Xingyuan Bian, Zongfeng Li, Junning Cui
This paper is to investigate the high-quality analytical reconstructions of multiple source-translation computed tomography (mSTCT) under an extended field of view (FOV). Under the larger FOVs, the previously proposed backprojection filtration (BPF) algorithms for mSTCT, including D-BPF and S-BPF (their differences are different derivate directions along the detector and source, respectively), make
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Enhancement based convolutional dictionary network with adaptive window for low-dose CT denoising J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-09-02 Yi Liu, Rongbiao Yan, Yuhang Liu, Pengcheng Zhang, Yang Chen, Zhiguo Gui
BACKGROUND:Recently, one promising approach to suppress noise/artifacts in low-dose CT (LDCT) images is the CNN-based approach, which learns the mapping function from LDCT to normal-dose CT (NDCT). However, most CNN-based methods are purely data-driven, thus lacking sufficient interpretability andoften losing details. OBJECTIVE:To solve this problem, we propose a deep convolutional dictionary learning
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Dual-energy micro-focus computed tomography based on the energy-angle correlation of inverse Compton scattering source J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-08-22 Yue Ma, Dexiang Liu, Jianfei Hua, Wei Lu
BACKGROUND:Inverse Compton scattering (ICS) source can produce quasi-monoenergetic micro-focus X-rays ranging from keV to MeV level, with potential applications in the field of high-resolution computed tomography (CT) imaging. ICS source has an energy-angle correlated feature that lower photon energy is obtained at larger emission angle, thus different photon energies are inherently contained in each
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CT imaging-based radiomics signatures improve prognosis prediction in postoperative colorectal cancer J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-08-18 Yan Kong, Muchen Xu, Xianding Wei, Danqi Qian, Yuan Yin, Zhaohui Huang, Wenchao Gu, Leyuan Zhou
OBJECTIVE:To investigate the use of non-contrast-enhanced (NCE) and contrast-enhanced (CE) CT radiomics signatures (Rad-scores) as prognostic factors to help improve the prediction of the overall survival (OS) of postoperative colorectal cancer (CRC) patients. METHODS:A retrospective analysis was performed on 65 CRC patients who underwent surgical resection in our hospital as the training set, and
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Dual-modal radiomics for predicting cervical lymph node metastasis in papillary thyroid carcinoma J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-08-17 Yongzhen Ren, Siyuan Lu, Dongmei Zhang, Xian Wang, Enock Adjei Agyekum, Jin Zhang, Qing Zhang, Feiju Xu, Guoliang Zhang, Yu Chen, Xiangjun Shen, Xuelin Zhang, Ting Wu, Hui Hu, Xiuhong Shan, Jun Wang, Xiaoqin Qian
BACKGROUND:Preoperative prediction of cervical lymph node metastasis (CLNM) in patients with papillary thyroid carcinoma (PTC) is significant for surgical decision-making. OBJECTIVE:This study aims to develop a dual-modal radiomics (DMR) model based on grayscale ultrasound (GSUS) and dual-energy computed tomography (DECT) for non-invasive CLNM in PTC. METHODS:In this study, 348 patients with pathologically
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Classification of esophageal cancer stage using an ensembled CNN with artificial bee colony optimization method and a SVM classifier J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-08-14 A. Chempak Kumar, D. Muhammad Noorul Mubarak
BACKGROUND:Esophageal cancer (EC) is aggressive cancer with a high fatality rate and a rapid rise of the incidence globally. However, early diagnosis of EC remains a challenging task for clinicians. OBJECTIVE:To help address and overcome this challenge, this study aims to develop and test a new computer-aided diagnosis (CAD) network that combines several machine learning models and optimization methods
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Development of a new body weight estimation method using head CT scout images J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-31 Tatsuya Kondo, Manami Umezu, Yohan Kondo, Mitsuru Sato, Tsutomu Kanazawa, Yoshiyuki Noto
BACKGROUND:Imaging examinations are crucial for diagnosing acute ischemic stroke, and knowledge of a patient’s body weight is necessary for safe examination. To perform examinations safely and rapidly, estimating body weight using head computed tomography (CT) scout images can be useful. OBJECTIVE:This study aims to develop a new method for estimating body weight using head CT scout images for contrast-enhanced
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Enhancing teeth segmentation using multifusion deep neural net in panoramic X-ray images J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-21 Saurabh Arora, Ruchir Gupta, Rajeev Srivastava
BACKGROUND:Precise teeth segmentation from dental panoramic X-ray images is an important task in dental practice. However, several issues including poor image contrast, blurring borders of teeth, presence of jaw bones and other mouth elements, makes reading and examining such images a challenging and time-consuming task for dentists. Thus, developing a precise and automated segmentation technique is
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Automated recognition of the major muscle injury in athletes on X-ray CT images 1 J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-21 Wanping Jia, Guangyong Zhao
Background:In this research, imaging techniques such as CT and X-ray are used to locate important muscles in the shoulders and legs. Athletes who participate in sports that require running, jumping, or throwing are more likely to get injuries such as sprains, strains, tendinitis, fractures, and dislocations. One proposed automated technique has the overarching goal of enhancing recognition. Objective:This
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Accelerating image reconstruction for multi-contrast MRI based on Y-Net3+ J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-13 Xin Cai, Xuewen Hou, Rong Sun, Xiao Chang, Honglin Zhu, Shouqiang Jia, Shengdong Nie
BACKGROUND:As one of the significant preoperative imaging modalities in medical diagnosis, Magnetic resonance imaging (MRI) takes a long scanning time due to its special imaging principle. OBJECTIVE:We propose an innovative MRI reconstruction strategy and data consistency method based on deep learning to reconstruct high-quality brain MRIs from down-sampled data and accelerate the MR imaging process
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A computational approach for analysis of intratumoral heterogeneity and standardized uptake value in PET/CT images 1 J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-13 Khalaf Alshamrani, Hassan A. Alshamrani
BACKGROUND:By providing both functional and anatomical information from a single scan, digital imaging technologies like PET/CT and PET/MRI hybrids are gaining popularity in medical imaging industry. In clinical practice, the median value (SUVmed) receives less attention owing to disagreements surrounding what defines a lesion, but the SUVmax value, which is a semi-quantitative statistic used to analyse
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Differences in apparent diffusion coefficient histogram analysis according to EGFR mutation status in brain metastasis due to lung adenocarcinoma J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-06 Ezel Yaltırık Bilgin, Özkan Ünal, Muhammed Fatih Göç, Taha Bahşi
BACKGROUND:The etiology, clinicopathological features, and prognosis of cancer in cases with EGFR mutations are different from those without mutations. OBJECTİVE:This study aims to evaluate the differences in ADC histogram analysis in brain metastases with EGFR mutation status in lung adenocarcinoma cases and the relationship between ADC histogram analysis differences and overall survival. METHODS:In
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An empirical method for geometric calibration of a photon counting detector-based cone beam CT system J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-06 Muhammad Usman Ghani, Andrey Makeev, Joseph A. Manus, Stephen J. Glick, Bahaa Ghammraoui
BACKGROUND:Geometric calibration is essential in developing a reliable computed tomography (CT) system. It involves estimating the geometry under which the angular projections are acquired. Geometric calibration of cone beam CTs employing small area detectors, such as currently available photon counting detectors (PCDs), is challenging when using traditional-based methods due to detectors’ limited
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A fast tomosynthesis method for printed circuit boards based on a multiple multi-resolution reconstruction algorithm J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-04 Hui Tang, Tian Li, Yu Bing Lin, Yu Li, Xu Dong Bao
Digital tomosynthesis (DTS) technology has attracted much attention in the field of nondestructive testing of printed circuit boards (PCB) due to its high resolution and suitability to thin slab objects. However, the traditional DTS iterative algorithm is computationally demanding, and its real-time processing of high-resolution and large volume reconstruction is infeasible. To address this issue,
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Learning technology for detection and grading of cancer tissue using tumour ultrasound images 1 J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-03 Liyan Zhang, Ruiyan Xu, Jingde Zhao
BACKGROUND:Early diagnosis of breast cancer is crucial to perform effective therapy. Many medical imaging modalities including MRI, CT, and ultrasound are used to diagnose cancer. OBJECTIVE:This study aims to investigate feasibility of applying transfer learning techniques to train convoluted neural networks (CNNs) to automatically diagnose breast cancer via ultrasound images. METHODS:Transfer learning
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Automated lung tumor segmentation robust to various tumor sizes using a consistency learning-based multi-scale dual-attention network J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-03 Jumin Lee, Min-Jin Lee, Bong-Seog Kim, Helen Hong
BACKGROUND:It is often difficult to automatically segment lung tumors due to the large tumor size variation ranging from less than 1 cm to greater than 7 cm depending on the T-stage. OBJECTIVE:This study aims to accurately segment lung tumors of various sizes using a consistency learning-based multi-scale dual-attention network (CL-MSDA-Net). METHODS:To avoid under- and over-segmentation caused by
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CT-guided percutaneous microwave ablation for pulmonary metastases from colorectal cancer: Prognosis analyses based on the origin of the primary tumor J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-03 Yuting Huang, Ketong Wu, Yang Liu, Dan Li, Haiyang Lai, Tao Peng, Yuan Wan, Bo Zhang
BACKGROUND:Microwave ablation (MWA) is becoming an effective therapy for inoperable pulmonary metastases from colorectal cancer (CRC). However, it is unclear whether the primary tumor location affects survival after MWA. OBJECTIVE:This study aims to investigate the survival outcomes and prognosticfactors of MWA based on different primary origins between colon and rectal cancer. METHODS:Patients who
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Meta analysis of the second course of radiotherapy for recurrent esophageal cancer 1 J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-01 Pengcheng Xu, Yongsheng Liu, Shen Wu, Dong Cheng, Zhanfeng Sun
Abstract BACKGROUND: How to improve efficacy and reduce side effects in treating recurrent esophageal cancer by applying the second course of radiotherapy alone and its combination with chemotherapy has been attracting broad research interest. OBJECTIVE: This review paper aims to systematically evaluate efficacy and side effects of applying the second course of anterograde radiotherapy alone and its
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CLSSL-ResNet: Predicting malignancy of solitary pulmonary nodules from CT images by chimeric label with self-supervised learning J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-07-01 Tianhu Zhao, Shouliang Qi, Yong Yue, Baihua Zhang, Jinxu Li, Yanhua Wen, Yudong Yao, Wei Qian, Yubao Guan
BACKGROUND:Pulmonary granulomatous nodules (GN) with spiculation or lobulation have a similar morphological appearance to solid lung adenocarcinoma (SADC) under computed tomography (CT). However, these two kinds of solid pulmonary nodules (SPN) have different malignancies and are sometimes misdiagnosed. OBJECTIVE:This study aims to predict malignancies of SPNs by a deep learning model automatically
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Improvement of imaging and image correction methods for the soft X-ray projection microscopy J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-24 Vanchinkhuu Jigmeddorj, Erdenetogtokh Jamsranjav, Duurenbuyan Baatar, Yasuhito Kinjo, Atsushi Ito, Tatsuo Shiina
BACKGROUND:The soft X-ray projection microscope has been developed for high resolution imaging of hydrated bio-specimens. Image blurring due to X-ray diffraction can be corrected by an iteration procedure. The correction is not efficient enough for all images, especially for low contrast chromosomeimages. OBJECTIVE:The purpose of this study is to improve X-ray imaging techniques using a finer pinhole
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VDVM: An automatic vertebrae detection and vertebral segment matching framework for C-arm X-ray image identification J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-24 Ruyi Zhang, Yiwei Hu, Kai Zhang, Guanhua Lan, Liang Peng, Yabin Zhu, Wei Qian, Yudong Yao
BACKGROUND:C-arm fluoroscopy, as an effective diagnosis and treatment method for spine surgery, can help doctors perform surgery procedures more precisely. In clinical surgery, the surgeon often determines the specific surgical location by comparing C-arm X-ray images with digital radiography (DR)images. However, this heavily relies on the doctor’s experience. OBJECTIVE:In this study, we design a framework
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Comparison of four commercial dose calculation algorithms in different evaluation tests J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-24 Aram Rostami, Aluisio Jose De Castro Neto, Satheesh Prasad Paloor, Abdul Sattar Khalid, Rabih Wafiq Hammoud
Background:Accurate and fast dose calculation is crucial in modern radiation therapy. Four dose calculation algorithms (AAA, AXB, CCC, and MC) are available in Varian Eclipse and RaySearch Laboratories RayStation Treatment Planning Systems (TPSs). Objectives:This study aims to evaluate and comparedosimetric accuracy of the four dose calculation algorithms applying to homogeneous and heterogeneous media
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Set-up errors of the neck are underestimated using the overall registration frame of head and neck in IMRT for NPC J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-24 Xu Junjie, Wang Tong, Luo Yu, Shang Lintao, Mai Xiuying, Ruan Junjie, Pan Xiaofen, Chi Feng
Background:There is no standardized registration frame of cone beam CT (CBCT) in intensity modulated radiotherapy (IMRT) for nasopharyngeal carcinoma (NPC). The overall registration frame that covers the whole head and neck is the most used CBCT registration frame for NPC patients in IMRT. Objective:To compare the set-up errors using different registration frames of CBCT for NPC to assess accuracy
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Compound feature attention network with edge enhancement for low-dose CT denoising J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-19 Shubin Wang, Yi Liu, Pengcheng Zhang, Ping Chen, Zhiyuan Li, Rongbiao Yan, Shu Li, Ruifeng Hou, Zhiguo Gui
BACKGROUND:Low-dose CT (LDCT) images usually contain serious noise and artifacts, which weaken the readability of the image. OBJECTIVE:To solve this problem, we propose a compound feature attention network with edge enhancement for LDCT denoising (CFAN-Net), which consists of an edge-enhanced module and a proposed compound feature attention block (CFAB). METHODS:The edge enhancement module extracts
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Performance of deep learning in classifying malignant primary and metastatic brain tumors using different MRI sequences: A medical analysis study J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-17 Adam Fauzi, Yuyun Yueniwati, Agus Naba, Rachmi Fauziah Rahayu
BACKGROUND:Malignant Primary Brain Tumor (MPBT) and Metastatic Brain Tumor (MBT) are the most common types of brain tumors, which require different management approaches. Magnetic Resonance Imaging (MRI) is the most frequently used modality for assessing the presence of these tumors. The utilization of Deep Learning (DL) is expected to assist clinicians in classifying MPBT and MBT more effectively
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Research on accuracy of material identification based on photon counting spectral CT J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-06-10 Xiaomei Zhang, Zhe Wang, Xiangyu Yun, Mohan Li, Jinming Hu, Chengmin Wang, Cunfeng Wei
BACKGROUND:Photon counting spectral CT is a significant direction in the development of CT technology and material identification is an important application of spectral CT. However, spectrum estimation in photon counting spectral CT is highly complex and may affect quantification accuracy of material identification. OBJECTIVE:To address the problem of energy spectrum estimation in photon-counting
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Radiation exposure in cone beam CT measured using a MOSFET and RPLGD dosimeter and Monte Carlo simulation in phantom J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-05-25 Dae Cheol Kweon
BACKGROUND:Due to the wide application of the cone beam computed tomography (CBCT) in clinical practice, it is important to assess radiation dose of CBCT more accurately and efficiently in different clinical applications. OBJECTIVE:This study aims to calculate effective and absorbed doses in CBCT measured in an anthropomorphic phantom using computer-based Monte Carlo (PCXMC) software, and to conduct
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Application value of digital tungsten-molybdenum dual target three-dimensional positioning indwelling guide wire excision biopsy in diagnosis of breast microcalcification J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-05-22 Junmin Ma
OBJECTIVE:To explore the application value of digital tungsten-molybdenum double target three-dimensional positioning indwelling guide wire and guided surgical resection biopsy in the diagnosis of breast microcalcification. METHODS:A retrospective analysis of 168 patients with negative clinical palpation and molybdenum target X-ray examination found breast abnormalities were equally divided into two
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Dosimetric properties of PASSAG polymer gel dosimeter in electron beam radiotherapy using magnetic resonance imaging J. X-Ray Sci. Technol. (IF 3.0) Pub Date : 2023-05-19 Tiancheng Zhang, Yasir Q. Almajidi, Sameer A. Awad, Firas Rahi Alhachami, Maher Abdulfadhil Gatea, Wesam R. Kadhum
BACKGROUND:Several physical factors such as photon beam energy, electron beam energy, and dose rate may affect the dosimetric properties of polymer gel dosimeters. The photon beam energy and dose rate dependence of PASSAG gel dosimeter were previously evaluated. OBJECTIVE:This study aims to assessthe dosimetric properties of the optimized PASSAG gel samples in various electron beam energies. METHODS:The