BACKGROUND:A statistical method called maximum likelihood expectation maximization (MLEM) is quite attractive, especially in PET/SPECT. However, the convergence rate of the iterative scheme of MLEM is quite slow. OBJECTIVE:This study aims to develop and test a new method to speed up the convergencerate of the MLEM algorithm. METHODS:We introduce a relaxation parameter in the conventional MLEM iterative

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

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

Abstract Background: Accurate and rapid diagnosis of coronavirus disease (COVID-19) is crucial for timely quarantine and treatment. Purpose: In this study, a deep learning algorithm-based AI model using ResUNet network was developed to evaluate the performance of radiologists with and without AI assistance in distinguishing COVID-19 infected pneumonia patients from other pulmonary infections on CT

BACKGROUND:Thyroid ultrasonography is widely used to diagnose thyroid nodules in clinics. Automatic localization of nodules can promote the development of intelligent thyroid diagnosis and reduce workload of radiologists. However, besides the ultrasound image has low contrast and high noise, the thyroid nodules are diverse in shape and vary greatly in size. Thus, thyroid nodule detection in ultrasound

Dual-energy computed tomography (DECT) provides more anatomical and functional information for image diagnosis. Presently, the popular DECT imaging systems need to scan at least full angle (i.e., 360°). In this study, we propose a DECT using complementary limited-angle scan (DECT-CL) technology toreduce the radiation dose and compress the spatial distribution of the imaging system. The dual-energy

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

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 derivedformulas are applicable to setups with phase gratings of any phase modulation and with either monochromatic

BACKGROUND:Radiation risk from computed tomography (CT) is always an issue for patients, especially those in clinical conditions in which repeated CT scanning is required. For patients undergoing repeated CT scanning, a low-dose protocol, such as sparse scanning, is often used, and consequently, anadvanced reconstruction algorithm is also needed. OBJECTIVE:To develop a novel algorithm used for sparse-view

BACKGROUND:Dual-energy breast CT reconstruction has a potential application that includes separation of microcalcification from healthy breast tissue for assisting early breast cancer detection. OBJECTIVE:To investigate and validate the noise suppression algorithm applied in the decomposition of the simulated breast phantom into microcalcification and healthy breast. METHODS:The proposed hybrid optimization

BACKGROUND:Computed Tomographic (CT) imaging procedures have been reported as the main source of radiation in diagnostic procedures compared to other modalities. To provide the optimal quality of CT images at the minimum radiation risk to the patient, periodic inspections and calibration tests forCT equipment are required. These tests involve a series of measurements that are time consuming and may

BACKGROUND:Automatic segmentation of individual tooth root is a key technology for the reconstruction of the three-dimensional dental model from Cone Beam Computed Tomography (CBCT) images, which is of great significance for the orthodontic, implant and other dental diagnosis and treatment planning. OBJECTIVES:Currently, tooth root segmentation is mainly done manually because of the similar gray of

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 during the process of data acquisition, stationary DBT (s-DBT) was developed to allow the

Currently, cardiac computed tomography angiography (CTA) is widely applied to coronary artery disease diagnosis. Automatic segmentation of coronary artery has played an important role in coronary artery disease diagnosis. 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

BACKGROUND:Repeat CT scanning is ubiquitous in many clinical situations, e.g. to follow disease progression, to evaluate treatment efficacy, and to monitor interventional CT procedures. However, it incurs in cumulative radiation to the patient which can be significantly reduced by using a region ofinterest (ROI) and the existing baseline scan. OBJECTIVE:To obtain a high-quality reconstruction of a

BACKGROUND:Although rheumatoid arthritis (RA) causes destruction of articular cartilage, early treatment significantly improves symptoms and delays progression. It is important to detect subtle damage for an early diagnosis. Recent software programs are comparable with the conventional human scoring method regarding detectability of the radiographic progression of RA. Thus, automatic and accurate selection

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

OBJECTIVE:To study the diagnostic value of real-time ultrasound shear wave elastography (US-SWE) in evaluating the histological stages of nonalcoholic fatty liver disease (NAFLD) in a rabbit model. MATERIALS AND METHODS:Twenty-one 8-week-old rabbits were fed a high-fat, high-cholesterol diet (experimental groups), and seven rabbits were fed a standard diet (control group). All rabbits underwent real-time

Abstract OBJECTIVES: 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%)

BACKGROUND:Calcification is an important criterion for classification between benign and malignant thyroid nodules. Deep learning provides an important means for automatic calcification recognition, but it is tedious to annotate pixel-level labels for calcifications with various morphologies. OBJECTIVE:This study aims to improve accuracy of calcification recognition and prediction of its location,

BACKGROUND/OBJECTIVE:In this retrospective study, we aimed to investigate a new 3D evaluation method for evaluating bone regeneration after cystectomy of odontogenic cysts. METHODS:The study included 26 patients who underwent cystectomies between 2012 and 2017 and had received either fillings or non-fillings with autologous iliac crest. Bony regeneration was analyzed using 3D imaging software and comparing

OBJECTIVE:This study aims to employ the advantages of computer vision and medical image analysis to develop an automated model that has the clinical potential for early detection of novel coronavirus (COVID-19) infected disease. METHOD:This study applied transfer learning method to develop deep learning models for detecting COVID-19 disease. Three existing state-of-the-art deep learning models namely

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:

BACKGROUD AND OBJECTIVE:The control of clinical manifestation of vestibular system relies on an optimal diagnosis. This study aims to develop and test a new automated diagnostic scheme for vestibular disorder recognition. METHODS:In this study we stratify the Ellipse-fitting technique using the Video Nysta Gmographic (VNG) sequence to obtain the segmented pupil region. Furthermore, the proposed methodology

BACKGROUND:The novel coronavirus disease 2019 (COVID-19) constitutes a public health emergency globally. The number of infected people and deaths are proliferating every day, which is putting tremendous pressure on our social and healthcare system. Rapid detection of COVID-19 cases is a significantstep to fight against this virus as well as release pressure off the healthcare system. OBJECTIVE:One

Computed tomography (CT) has been widely applied in medical diagnosis, nondestructive evaluation, homeland security, and other science and engineering applications. Image reconstruction is one of the core CT imaging technologies. In this review paper, we systematically reviewed the currently publicly available CT image reconstruction open source toolkits in the aspects of their environments, object

OBJECTIVE:Several physical factors such as dose rate and photon energy may change response and sensitivity of polymer gel dosimeters. This study aims to evaluate the R2-dose response and sensitivity dependence of PASSAG-U gel dosimeters with 3% and 5% urea on dose rate and photon energy. MATERIALSAND METHODS:The PASSAG-U gel dosimeters were prepared under normal atmospheric conditions. The obtained

BACKGROUND:Brain tumor segmentation plays an important role in assisting diagnosis of disease, treatment plan planning, and surgical navigation. OBJECTIVE:This study aims to improve the accuracy of tumor boundary segmentation using the multi-scale U-Net network. METHODS:In this study, a novel U-Netwith dilated convolution (DCU-Net) structure is proposed for brain tumor segmentation based on the classic

The automatic classification of breast cancer pathological images has important clinical application value. However, to develop the classification algorithm using the artificially extracted image features faces several challenges including the requirement of professional domain knowledge to extractand compute highiquality image features, which are often time-consuming, laborious, and difficult. For

OBJECTIVE:This study aims to analyze and compare the diagnostic effectiveness of 320-row multi-detector computed tomography for coronary artery angiography (MDCTA) in subjects with and without sublingual vasodilator (nitroglycerin). MATERIALS AND METHODS:From September 2015 to September 2016, 70 individuals without history of major cardiovascular diseases who underwent MDCTA for health examination

OBJECTIVES:To assess prognosis or dynamic change from initial diagnosis until recovery of the patients with moderate coronavirus disease (COVID-19) pneumonia using chest CT images. MATERIALS AND METHODS:In this retrospective study, 33 patients (18 men, 15 women; median age, 49.0 years) with confirmed with moderate COVID-19 pneumonia in a multicenter hospital were included. The patients underwent at

PURPOSE:To evaluate the influence of iterative reconstruction (IR) levels on Computed Tomography (CT) image quality and to establish Figure of Merit (FOM) value for CT Pulmonary Angiography (CTPA) examinations. METHODS:Images of 31 adult patients who underwent CTPA examinations in our institution from March to April 2019 were retrospectively collected. Other data, such as scanning parameters, radiation

BACKGROUND:Multi-modal medical image fusion plays a crucial role in many areas of modern medicine like diagnosis and therapy planning. OBJECTIVE:Due to the factor that the structure tensor has the property of preserving the image geometry, we utilized it to construct the directional structure tensor and further proposed an improved 3-D medical image fusion method. METHOD:The local entropy metrics were

In this article, we analyze and report cases of three patients who were admitted to Renmin Hospital, Wuhan University, China, for treating COVID-19 pneumonia in February 2020 and were unresponsive to initial treatment of steroids. They were then received titrated steroids treatment based on the assessment of computed tomography (CT) images augmented and analyzed with the artificial intelligence (AI)

It is of great importance to study the alignment of atoms in collision process in elementary analysis with a Particle Induced X-ray Emission (PIXE) technique. The measurement of alignment can also offer an effective testing ground for developing theory models in ionization process. The typical L X-ray spectra are measured for Ag thin target by 15 keV electron impact at emission angles from 0° to 25°

OBJECTIVE:Diagnosis of tuberculosis (TB) on multi-slice spiral computed tomography (CT) images is a difficult task in many TB prevalent locations in which experienced radiologists are lacking. To address this difficulty, we develop an automated detection system based on artificial intelligence (AI)in this study to simplify the diagnostic process of active tuberculosis (ATB) and improve the diagnostic

BACKGROUND:Osteoporosis, a silent killing disease of fracture risk, is normally determined based on the bone mineral density (BMD) and T-score values measured in bone. However, development of standard algorithms for accurate segmentation and BMD measurement from X-ray images is a challenge in the medical field. OBJECTIVE:The purpose of this work is to more accurately measure BMD from X-ray images,

Human eye is affected by the different eye diseases including choroidal neovascularization (CNV), diabetic macular edema (DME) and age-related macular degeneration (AMD). This work aims to design an artificial intelligence (AI) based clinical decision support system for eye disease detection and classification to assist the ophthalmologists more effectively detecting and classifying CNV, DME and drusen

BACKGROUND:Triple-energy computed tomography (TECT) can obtain x-ray attenuation measurements at three energy spectra, thereby allowing identification of different material compositions with same or very similar attenuation coefficients. This ability is known as material decomposition, which can decompose TECT images into different basis material image. However, the basis material image would be severely

BACKGROUND:Although computed tomography (CT) is a powerful diagnostic imaging modality for diagnosing vascular diseases, it is some what risky to human health due to the high radiation dosage. Thus, CT vendors have developed low dose computed tomography (LDCT) aiming to solve this problem. Nowadays, LDCT has gradually become a main stream of CT examination. OBJECTIVE:This study aimed to assess the

BACKGROUND:In regular examinations, it may be difficult to visually identify benign and malignant liver tumors based on plain computed tomography (CT) images. RCAD (radiomics-based computer-aided diagnosis) has proven to be helpful and provide interpretability in clinical use. OBJECTIVE:This work aims to develop a CT-based radiomics signature and investigate its correlation with malignant/benign liver

BACKGROUND:Lung cancer is one of the most common diseases in the world. Computed tomography (CT) is the standard medical modality for early lung nodule detection and diagnosis that improves patient’s survival rate. Recently, deep learning algorithms, especially convolutional neural networks (CNNs),have become a preferred methodology for developing computer-aided detection and diagnosis (CAD) schemes

BACKGROUND:Pneumonia caused by COVID-19 shares overlapping imaging manifestations with other types of pneumonia. How to objectively and quantitatively differentiate pneumonia patients with and without COVID-19 virus remains clinical challenge. OBJECTIVE:To formulate standardized scoring criteria and an objective quantization standard to guide decision making in detection and diagnosis of COVID-19 virus

Meningioma is among the most common primary tumors of the brain. The firmness of Meningioma is a critical factor that influences operative strategy and patient counseling. Conventional methods to predict the tumor firmness rely on the correlation between the consistency of Meningioma and their preoperative MRI findings such as the signal intensity ratio between the tumor and the normal grey matter

OBJECTIVE:To evaluate the utility of radiomics analysis for differentiating benign and malignant epithelial salivary gland tumors on diffusion-weighted imaging (DWI). METHODS:A retrospective dataset involving 218 and 51 patients with histology-confirmed benign and malignant epithelial salivary gland tumors was used in this study. A total of 396 radiomic features were extracted from the DW images. Analysis

INTRODUCTION:Testicular infarction is a rare complication of prolonged epididymitis and may be misdiagnosed as testicular torsion. In this study, we present three cases of testicular infarction and discuss their clinical characteristics, imaging features and clinical management. PATIENTS AND METHODS:Three adult males with prolonged epididymitis presented with chronic unilateral testicular pain, tenderness

The objective of this study is to determine X-ray dose distribution and the correlation between central, peripheral and weighted-centre peripheral doses for various phantom sizes and tube voltages in computed tomography (CT). We used phantoms developed in-house, with various water-equivalent diameters (Dw) from 8.5 up to 42.1 cm. The phantoms have one hole in the centre and four holes at the periphery

Abstract OBJECTIVE: To evaluate the clinical and computed tomographic (CT) features in the patients with COVID-19 pneumonia confirmed by the real-time reverse transcriptase polymerase chain reaction (rRT-PCR) amplification of the viral DNA from a sputum sample. MATERIAL AND METHODS: Clinical information and CT findings of a total of 14 patients with COVID-19 infection (age range, 12–83 years; females

Abstract PURPOSE: To analyze clinical and thin-section computed tomographic (CT) data from the patients with coronavirus disease (COVID-19) to predict the development of pulmonary fibrosis after hospital discharge. MATERIALS AND METHODS: Fifty-nine patients (31 males and 28 females ranging from 25 to 70 years old) with confirmed COVID-19 infection performed follow-up thin-section thorax CT. After 31

Abstract Recently, COVID-19 has spread in more than 100 countries and regions around the world, raising grave global concerns. COVID-19 transmits mainly through respiratory droplets and close contacts, causing cluster infections. The symptoms are dominantly fever, fatigue, and dry cough, and can be complicated with tiredness, sore throat, and headache. A few patients have symptoms such as stuffy nose

BACKGROUND:High-resolution, low-noise detectors with minimal dead-space at chest-wall could improve posterior coverage and microcalcification visibility in the dedicated cone-beam breast CT (CBBCT). However, the smaller field-of-view necessitates laterally-shifted detector geometry to enable optimizing the air-gap for x-ray scatter rejection. OBJECTIVE:To evaluate laterally-shifted detector geometry

Recently, lung cancer has been paid more and more attention. People have reached a consensus that early detection and early treatment can improve the survival rate of patients. Among them, pulmonary nodules are the important reference for doctors to determine the lung health. With the continuous improvement of CT image resolution, more suspected pulmonary nodule information appears from the impact

PURPOSE:To predict programmed death-ligand 1 (PD-L1) expression of tumor cells in non-small cell lung cancer (NSCLC) patients by using a radiomics study based on CT images and clinicopathologic features. MATERIALS AND METHODS:A total of 390 confirmed NSCLC patients who performed chest CT scan and immunohistochemistry (IHC) examination of PD-L1 of lung tumors with clinic data were collected in this

OBJECTIVE:Since in-house phantoms may provide effective quality control for gamma cameras in clinical settings, this study aims to assess an in-house phantom designed to perform quality control tests of a gamma camera using locally available, affordable materials. This is of particular importance in developing countries where scientific support may not be readily available. MATERIALS AND METHODS:The

BACKGROUND:Surgery is usually recommended to treat retroperitoneal tumors. However, complete surgical resections often remain challenging. OBJECTIVE:To assess the assistant role of three-dimensional (3D) imaging and printing model in retroperitoneal tumor resection, as well as compare the difference between 3D printing and computed tomography (CT) in preoperative planning and confidence building. METHODS:We

In this paper, we present a review of the research literature regarding applying X-ray imaging of baggage scrutiny at airport. It discusses multiple X-ray imaging inspection systems used in airports for detecting dangerous objects inside the baggage. Moreover, it also explains the dual energy X-rayimage fusion and image enhancement factors. Different types of noises in digital images and noise models

BACKGROUND:Threat Image Projection (TIP) is a technique used in X-ray security baggage screening systems that superimposes a threat object signature onto a benign X-ray baggage image in a plausible and realistic manner. It has been shown to be highly effective in evaluating the ongoing performanceof human operators, improving their vigilance and performance on threat detection. OBJECTIVE:With the increasing

BACKGROUND Diagnostic quality of computed tomography (CT) images depends on numerous factors. Recently, two different modalities were introduced for coronary CT angiography (CCTA). OBJECTIVE This study aims to compare the performance of 16 cm wide-coverage detector CT (WDCT) using the snapshot freeze technique with a new-generation dual-source CT (DSCT) with 66 ms temporal resolution for CCTA. METHODS

OBJECTIVE To evaluate the diagnostic value of ultrasonography and mammography for plasma cell mastitis. METHODS The ultrasonographic and mammographic images of 111 women with histopathologically confirmed plasma cell mastitis were retrospectively analyzed. The diagnostic accuracy of the two imaging methods was compared. RESULTS Ultrasonography identified 91 out of 111 (82.0%) patients with plasma cell

OBJECTIVE To compare the clinical effectiveness of ultrasound-guided corticosteroid injection with and without needle release of the A1 pulley in treating trigger finger. METHODS A total of 60 patients with trigger finger were enrolled in this retrospective study. Among them, 30 patients were treated with ultrasound-guided needle release of the A1 pulley with corticosteroid injection (group A) and