BACKGROUND:Interest exists in dual-energy computed tomography (DECT) imaging with scanning arcs of limited-angular ranges (LARs) for reducing scan time and radiation dose, and for enabling scan configurations of C-arm CT that can avoid possible collision between the rotating X-ray tube/detector andthe imaged subject. OBJECTIVE:In this work, we investigate image reconstruction for a type of configurations

OBJECTIVE:To assess clinical application of applying deep learning image reconstruction (DLIR) algorithm to contrast-enhanced portal venous phase liver computed tomography (CT) for improving image quality and lesions detection rate compared with using adaptive statistical iterative reconstruction (ASIR-V) algorithm under routine dose. METHODS:The raw data from 42 consecutive patients who underwent

OBJECTIVE:To evaluate dose differences predicted between using Anisotropic Analytical Algorithm (AAA) and Acuros XB (AXB) in patients diagnosed with locally advanced non-small cell lung cancer (NSCLC) treated with intensity modulated radiation therapy (IMRT). METHODS:A phantom study was done to evaluate the dose prediction accuracy of AXB and AAA beyond low-density medium by comparing the calculated

BACKGROUND:The limited-angle reconstruction problem is of both theoretical and practical importance. Due to the severe ill-posedness of the problem, it is very challenging to get a valid reconstructed result from the known small limited-angle projection data. The theoretical ill-posedness leads thenormal equation A T Ax = A T b of the linear system derived by discretizing the Radon transform to be

OBJECTIVE:To compare and evaluate diagnostic capabilities of preoperative ultrasonography (US) and magnetic resonance imaging (MRI) in the cervical lymph nodes of patients with papillary thyroid cancer. METHODS:A retrospective dataset involving 156 patients who had undergone thyroidectomy and preoperative US and MRI was assembled. Among these, 69 had cervical lymph node metastasis and 87 did not. At

Limited-angle computed tomography (CT) may appear in restricted CT scans. Since the available projection data is incomplete, the images reconstructed by filtered back-projection (FBP) or algebraic reconstruction technique (ART) often encounter shading artifacts. However, using the anisotropy property of the shading artifacts that coincide with the characteristic of limited-angle CT images can reduce

Precise segmentation of lung parenchyma is essential for effective analysis of the lung. Due to the obvious contrast and large regional area compared to other tissues in the chest, lung tissue is less difficult to segment. Special attention to details of lung segmentation is also needed. To improvethe quality and speed of segmentation of lung parenchyma based on computed tomography (CT) or computed

OBJECTIVE:To evaluate diagnostic value of Thyroid Imaging Reporting and Data System published by American College of Radiology (ACR TI-RADS) in 2017, ultrasound-guided fine-needle aspiration (US-FNA), and the combination of both methods in differentiation between benign and malignant thyroid nodules. METHODS:The data of US-FNA and ACR TI-RADS are collected from 159 patients underwent thyroid surgery

World-Health-Organization (WHO) has listed Tuberculosis (TB) as one among the top 10 reasons for death and an early diagnosis will help to cure the patient by giving suitable treatment. TB usually affects the lungs and an accurate bio-imaging scheme will be apt to diagnose the infection. This research aims to implement an automated scheme to detect TB infection in chest radiographs (X-ray) using a

BACKGROUND:The distribution of pulmonary vessels in computed tomography (CT) and computed tomography angiography (CTA) images of lung is important for diagnosing disease, formulating surgical plans and pulmonary research. PURPOSE:Based on the pulmonary vascular segmentation task of International Symposium on Image Computing and Digital Medicine 2020 challenge, this paper reviews 12 different pulmonary

OBJECTIVE:To improve safety and efficiency of radiotherapy process by customizing a Varian ARIA oncology information system following the guidelines provided in AAPM TG-100 report. METHODS:First, failure mode and effects analysis (FMEA) and quality management program were implemented for radiotherapy process. We have customized the visual care path in the ARIA system and set up a series of templates

Abstract BACKGROUND AND OBJECTIVE: Monitoring recovery process of coronavirus disease 2019 (COVID-19) patients released from hospital is crucial for exploring residual effects of COVID-19 and beneficial for clinical care. In this study, a comprehensive analysis was carried out to clarify residual effects of COVID-19 on hospital discharged patients. METHODS: Two hundred sixty-eight cases with laboratory

Repetitive transcranial magnetic stimulation (rTMS) of the brain is an effective clinical treatment for psychiatric disorders. Noninvasive neuroimaging during rTMS allows visualization of cortical brain activations and responses, and it is a potential tool for investigating the neurophysiological response occurring actively during stimulation. In this paper, we present a fast diffuse optical tomography

Reducing X-ray radiation is beneficial for reducing the risk of cancer in patients. There are two main approaches for achieving this goal namely, one is to reduce the X-ray current, and another is to apply sparse-view protocols to do image scanning and projections. However, these techniques usuallylead to degradation of the reconstructed image quality, resulting in excessive noise and severe edge artifacts

BACKGROUND AND OBJECTIVE:Estimates of parameters used to select patients for endovascular thrombectomy (EVT) for acute ischemic stroke differ among software packages for automated computed tomography (CT) perfusion analysis. To determine impact of these differences in decision making, we analyzed intra-observer and inter-observer agreement in recommendations about whether to perform EVT based on perfusion

BACKGROUND:The corpus callosum in the midsagittal plane plays a crucial role in the early diagnosis of diseases. When the anisotropy of the diffusion tensor in the midsagittal plane is calculated, the anisotropy of corpus callosum is close to that of the fornix, which leads to blurred boundary of the segmentation region. OBJECTIVE:To apply a fuzzy clustering algorithm combined with new spatial information

PURPOSE:Total Variation (TV) minimization algorithm is a classical compressed sensing (CS) based iterative image reconstruction algorithm that can accurately reconstruct images from sparse-view projections in computed tomography (CT). However, the system matrix used in the algorithm is often too large to be stored in computer memory. The purpose of this study is to investigate a new TV algorithm based

BACKGROUND:The time of flight (TOF) cone beam computed tomography (CBCT) was recently shown to reduce the X-ray scattering effects by 95%and improve the image CNR by 110%for large volume objects. The advancements in X-ray sources like in compact Free Electron Lasers (FEL) and advancements in detector technology show potential for the TOF method to be feasible in CBCT when imaging large objects. OBJECTIVE:To

Tuberculosis (TB) is a major health issue with high mortality rates worldwide. Recently, tremendous researches of artificial intelligence (AI) have been conducted targeting at TB to reduce the diagnostic burden. However, most researches are conducted in the developed urban areas. The feasibility ofapplying AI in low-resource settings remains unexplored. In this study, we apply an automated detection

OBJECTIVE:To develop an ensemble a deep transfer learning model of CT images for predicting pathologic complete response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). METHODS:The data were obtained from the public dataset ‘QIN-Breast’ from The Cancer Imaging Archive (TCIA). CT Images were gathered before and after the first cycle of NAC. CT images of 121 breast cancer patients

OBJECTIVES:To evaluate skin dose differences between TPS (treatment planning system) calculations and TLD (thermo-luminescent dosimeters) measurements along with the dosimetric effect of applicator misplacement for patients diagnosed with gynecological (GYN) cancers undergoing brachytherapy. METHODS:The skin doses were measured using TLDs attached in different locations on patients’ skin in pelvic

BACKGROUND:Pencil beam X-ray luminescence computed tomography (XLCT) imaging provides superior spatial resolution than other imaging geometries like sheet beam and cone beam geometries. However, the pencil beam geometry suffers from long scan times, resulting in concerns overdose which discouragesthe use of pencil beam XLCT. OBJECTIVE:The dose deposited in pencil beam XLCT imaging was investigated

OBJECTIVE:To develop and validate a radiomics model based on contrast-enhanced spectral mammography (CESM), and preoperatively discriminate low-grade (grade I/II) and high-grade (grade III) invasive breast cancer. METHOD:A total of 205 patients with CESM examination and pathologically confirmed invasive breast cancer were retrospectively enrolled. We randomly divided patients into two independent sets

BACKGROUND:Low-tube voltage scanning improves CT attenuation value of contrast medium (CM). Thus, we hypothesized that 70 kVp in pediatric abdominal CT angiography (CTA) could be used to reduce both radiation and CM dose and improve patient comfort at the same time. OBJECTIVE:To evaluate the feasibility of using 70 kVp in pediatric abdominal CTA to reduce radiation dose and CM dose and improve patient

OBJECTIVE:To investigate three-dimensional soft tissue changes of lips and related jaw changes in patients with skeletal class III malocclusion and facial asymmetry using cone-beam computerized tomography (CBCT). METHOD:This study included 46 CBCT scans of patients with aforementioned character before (T1) and 6–12 months after orthognathic surgery (T2). Subjects were divided into 2 groups according

OBJECTIVE:To explore the value of virtual touch imaging and quantification (VTIQ) shear wave elastography (SWE) in diagnosis of supraspinatus tendon tear. METHODS:Eighty patients with unilateral supraspinatus tendon tear underwent shoulder arthroscopy were prospective studied. Tendinopathy, partial-thickness tear or full-thickness tear of supraspinatus tendon were diagnosed according 2D ultrasound

OBJECTIVE:To investigate feasibility of applying deep learning image reconstruction (DLIR) algorithm in a low-kilovolt enhanced scan of the upper abdomen. METHODS:A total of 64 patients (BMI<28) are selected for the enhanced upper abdomen scan and divided evenly into two groups. The tube voltages in Group A are 100kV in arterial phase and 80kV in venous phase, while tube voltages are 120kV during two

OBJECTIVE:To assess the feasibility of using virtual non-contrast (VNC) images derived from dual-energy computed tomography (DECT) to replace true non-contrast (TNC) images of papillary thyroid carcinoma (PTC) patients. METHODS:Images of 96 PTC patients were retrospectively analyzed. TNC images were acquired under the single-energy mode of DECT after the plain scanning. The arterial and venous phase

Due to the limitation of dynamic range of the imaging device, the fixed-voltage X-ray images often produce overexposed or underexposed regions. Some structure information of the composite steel component is lost. This problem can be solved by fusing the multi-exposure X-ray images taken by using different voltages in order to produce images with more detailed structures or information. Due to the lack

PURPOSE:To investigate feasibility of predicting Lauren type of gastric cancer based on CT radiomics nomogram before operation. MATERIALS AND METHODS:The clinical data and pre-treatment CT images of 300 gastric cancer patients with Lauren intestinal or diffuse type confirmed by postoperative pathology were retrospectively analyzed, who were randomly divided into training set and testing set with a

Medical image segmentation is a key step to assist diagnosis of several diseases, and accuracy of a segmentation method is important for further treatments of different diseases. Different medical imaging modalities have different challenges such as intensity inhomogeneity, noise, low contrast, andill-defined boundaries, which make automated segmentation a difficult task. To handle these issues, we

OBJECTIVES:This study aims to evaluate diagnostic performance of radiomic analysis using computed tomography (CT) to identify lymphovascular invasion (LVI) in patients diagnosed with rectal cancer and assess diagnostic performance of different lesion segmentations. METHODS:The study is applied to 169 pre-treatment CT images and the clinical features of patients with rectal cancer. Radiomic features

BACKGROUND:Traditionally, X-ray systems for capturing moving objects consist of a continuous X-ray source and a detector that operates at a predetermined frame rate. OBJECTIVE:This study investigates the possibility of using pulsed X-ray source with an inductive energy storage device and a semiconductor opening switch for shooting moving objects. METHODS:The study uses a high-voltage pulse generator

BACKGROUND:Acute ischemic stroke (AIS) results in high morbidity, disability, and mortality. Early and automatic diagnosis of AIS can help clinicians administer the appropriate interventions. OBJECTIVE:To develop a deep symmetric 3D convolutional neural network (DeepSym-3D-CNN) for automated AIS diagnosis via diffusion-weighted imaging (DWI) images. METHODS:This study includes 190 study subjects (97

The Tc-99m methylene diphosphonate (MDP) whole body bone scan (WBBS) has been widely accepted as a method of choice for the initial diagnosis of bone and joint changes in patients with oncologic diseases. The WBBS has shown high sensitivity but relatively low specificity due to bone variation. Thisstudy aims to use the self-developing irregular flux viewer (IFV) system to predict possible bone lesions

PURPOSE:This study aims to evaluate the planned dose of stereotactic body radiation therapy (SBRT) for treating early peripheral non-small cell lung cancer (NSCLC) using the non-coplanar radiation from Cyberknife and Varian linac. Moreover, this study investigates whether Cyberknife and Varian linac are qualified for non-coplanar radiation SBRT for treating early peripheral NSCLC, and which one is

BACKGROUND:Digital radiography (DR) is grayscale adjustable and it can be unclear whether an acquired DR image is captured with the minimum radiation dose required. It is necessary to make an image of the amount of noise when taken at a lower dose than the acquired image, without increased exposure. OBJECTIVE:To examine whether an image of unacquired dose can be created from two types of dose DR images

BACKGROUND AND OBJECTIVE:Since the stair artifacts may affect non-destructive testing (NDT) and diagnosis in the later stage, an applicable model is desperately needed, which can deal with the stair artifacts and preserve the edges. However, the classical total variation (TV) algorithm only considers the sparsity of the gradient transformed image. The objective of this study is to introduce and test

BACKGROUND:Coronary computed tomography angiography (CCTA) is a noninvasive imaging modality to detect and diagnose coronary artery disease. Due to the limitations of equipment and the patient’s physiological condition, some CCTA images collected by 64-slice spiral computed tomography (CT) have motion artifacts in the right coronary artery, left circumflex coronary artery and other positions. OBJECTIVE:To

OBJECTIVE:In order to solve the blurred structural details and over-smoothing effects in sparse representation dictionary learning reconstruction algorithm, this study aims to test sparse angle CT reconstruction with weighted dictionary learning algorithm based on adaptive Group-Sparsity Regularization (AGSR-SART). METHODS:First, a new similarity measure is defined in which Covariance is introduced

PURPOSE:The adaptive steepest descent projection onto convex set (ASD-POCS) algorithm is a promising algorithm for constrained total variation (TV) type norm minimization models in computed tomography (CT) image reconstruction using sparse and/or noisy data. However, in ASD-POCS algorithm, the existing gradient expression of the TV-type norm appears too complicated in the implementation code and reduces

OBJECTIVE:To demonstrate the ability of achieving low dose and high-quality head CT images for children with acute head trauma using 100 kVp and adaptive statistical iterative reconstruction (ASIR-V) algorithm in single rotation on a 16 cm wide-detector system. MATERIALS AND METHODS:We retrospectively analyzed the CT dose index (CTDI) and image quality of 104 children aged 0–6 years with acute head

Multi-modal image fusion techniques aid the medical experts in better disease diagnosis by providing adequate complementary information from multi-modal medical images. These techniques enhance the effectiveness of medical disorder analysis and classification of results. This study aims at proposing a novel technique using deep learning for the fusion of multi-modal medical images. The modified 2D

OBJECTIVES:To investigate whether the baseline apparent diffusion coefficient (ADC) can predict survival in the hepatocellular carcinoma (HCC) patients receiving chemoembolization. MATERIALS AND METHODS:Diffusion-weighted MR imaging of HCC patients is performed within 2 weeks before chemoembolization. The ADC of the largest index lesion is recorded. Responses are assessed by mRECIST after the start

BACKGROUND:Virtual radiographic simulation has been found educationally effective for students to practice their clinical examinations remotely or online. A free available virtual simulator-ImaSim has received particular attention for radiographic science education because of its portability, freeof charge and no constrain of location and physical facility. However, it lacks evidence to validate this

BACKGROUND:With the rapid development of deep learning, several neural network models have been proposed for automatic segmentation of prohibited items. These methods usually based on a substantial amount of labelled training data. However, for some prohibited items of rarely appearing, it is difficult to obtain enough labelled samples. Furthermore, the category of prohibited items varies in different

INTRODUCTION:It is a challenge to make accurate pre-surgical diagnosis for renal tumors. This study is to report the findings, management, and outcome of one rare case of ossification in a cystic renal mass. We present and discuss the pathological characteristics, radiologic features, and treatmentalternatives of the patient. PATIENTS AND METHODS:A 38 years old female patient had intermittent epigastric

BACKGROUND:CT-derived fractional flow reserve (FFRCT) and diagnostic accuracy rely on good image quality during coronary CT angiography (CCTA). OBJECTIVE:To investigate whether heart rate (HR) and coronary artery calcium (CAC) score decrease image quality and diagnostic performance of two advancedCT scanners including 96-row detector dual source CT (DSCT) and 256-row multidetector CT (MDCT). METHODS:First

This study analyzes the response of increasing radiation dose to the pork tenderloin tissue. Considering its significant cell structure, pork tenderloin tissue samples are selected for the experimental objects to measure their electrical impedance characteristics. This study proposes and investigates an effective approach to characterize the variation of the internal change of the components of pork

OBJECTIVE:To explore the potential value of quantitative parameters derived from dual-energy spectral computed tomography (DESCT) as comparing to the parameters derived from magnetic resonance imaging (MRI) in detecting bone marrow (BM) infiltration and distinguishing different patterns of BM infiltration in patients diagnosed with Multiple myeloma (MM). METHODS:This study involved 35MM patients and

OBJECTIVE:To investigate relationship between the diffusion indexes of corticospinal tract (CST) and the neurological motor outcomes in chronic pontine stroke patients. METHODS:Diffusion tensor imaging (DTI) is performed in 27 patients with chronic pontine stroke. Fractional anisotropy (FA) valuesalong the CST area, the track number, and the CST length are measured. Neurological and motor outcomes

BACKGROUND:Materials characterization made possible by dual energy CT (DECT) scanners is expected to considerably improve automatic detection of hazardous objects in checked and carry-on luggage at our airports. Training a computer to identify the hazardous items from DECT scans however implies training on a baggage dataset that can represent all the possible ways a threat item can packed inside a

OBJECTIVES: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

Abstract BACKGROUND AND OBJECTIVE: Radiomics has been widely used in quantitative analysis of medical images for disease diagnosis and prognosis assessment. The objective of this study is to test a machine-learning (ML) method based on radiomics features extracted from chest CT images for screening COVID-19 cases. METHODS: The study is carried out on two groups of patients, including 138 patients with

BACKGROUND:Metal oxide glass composites have attracted huge interest as promising shielding materials to replace toxic, heavy, and costly conventional shielding materials. OBJECTIVE:In this work, we evaluate shielding effectiveness of four novel tellurite-based glasses samples doped with oxide metals (namely, A, B, C, and D, which are 75TeO2- 10P2O5- 10ZnO- 5PbF2- 0.24Er2O3 ; 70TeO2- 10P2O5- 10ZnO-

Abstract BACKGROUND: Recent occurrence of the 2019 coronavirus disease (COVID-19) outbreak, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has highlighted the need for fast, accurate, and simple strategies to identify cases on a large scale. OBJECTIVE: This study aims to develop and test an accurate detection and severity classification methodology that may help medical

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)

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

OBJECTIVE:In this study, we present an appropriate angle of incidence to reduce the distortions in images of L4 and L5 during a general anteroposterior radiograph examination. METHOD:We selected 170 patients who had normal radiological findings among those who underwent anteroposterior and lateralexamination for lumbar vertebrae. An optimum angle of incidence wa suggested through the statistical analysis

BACKGROUND:Since Gleason score (GS) 4 + 3 prostate cancer (PCa) has the worse prognosis than GS 3 + 4 PCa, differentiating these two types of PCa is of clinical significance. OBJECTIVE:To assess the predictive roles of using T2WI and ADC-derived image texture parameters in differentiating GS 3 + 4from GS 4 + 3 PCa. METHODS:Forty-eight PCa patients of GS 3 + 4 and 37 patients of GS 4 + 3 are retrieved