Evaluation of Positive Predictive Value for Digital Panoramic Radiography in Comparison to Ultrasound in the Diagnosis of Calcified Carotid Atheroma

Aim: Detection of calcified carotid atheroma (CCA) has an important role in reducing the incidence of Cerebro Vascular Accident (CVA). The aim of this study was to evaluate efficacy of panoramic digital radiography in detecting atherosclerosis. Methods: It is descriptive-analytical diagnostic study. The people (22 to 62 years old) were referred to a radiology clinic to perform panoramic radiography for diagnosis of CCA. Individuals who were suspected were introduced to the radiology department of dental school to undergo ultrasound evaluation to CCA. For the 41 patients (55 sides), ultrasound was performed. For data analysis, the Chi-square and Fisher's exact test were used. Results: The prevalence of CCA was 2.43%. The PPV of digital panoramic was 45.5%. There was no significant relationship between age (P = 0.14) and sex (P = 0.539) and PPV of digital panoramic. The PPV of digital panoramic was significantly associated with hypertension (P = 0.032). Conclusion: It seems that panoramic can be used to screen patients with a history of hypertension for atherosclerosis.

Relevance and Compliance of Requests for Dental Panoramic Radiography Examination at Yaounde (Cameroon)

Background: Research studies made in Cameroon on compliance and relevance in the various areas of imaging, show the failure to comply with administrative and clinical criteria. These research studies led to recommendations meant for result amelioration. However, the orthopantomogram (OPT) field remains less studied in that regard in Cameroon. Aim: Evaluate the relevance and compliance of examination requests for panoramic dental radiography. Setting and Design: It is a descriptive cross-sectional study with a consecutive sample of dental panoramic requests identified during the study period in 4 radiology centres of Yaoundé. Material and Methods: Variables studied here were the validity criteria of imaging examination. Request: Five of which are of administrative order (date of the request, requesting department, patient’s identity, patient’s age, applicant’s identity) and three of clinical order (anatomic region, reason for the examination and the purpose of the examination). Statistical Analysis: Chi-squared test was used with confidence interval of 95%. Results: Patient’s identity (name) was the criteria carrying the highest information (98.9%), followed by the name of the applicant physician (91.6%). Out of 179 requests analysed, 8.6% had complete information. 46.4% of requests had no indications. Dental surgeon was the top prescriber with a total of 112 (62.6%). Conclusion: The quality of dental panoramic requests was not optimal in Yaounde, with lack of precision mostly noted at the level of clinical criteria.

Radiography Image Classification Using Deep Convolutional Neural Networks

Research has shown that chest radiography images of patients with different diseases, such as pneumonia, COVID-19, SARS, pneumothorax, etc., all exhibit some form of abnormality. Several deep learning techniques can be used to identify each of these anomalies in the chest x-ray images. Convolutional neural networks (CNNs) have shown great success in the fields of image recognition and image classification since there are numerous large-scale annotated image datasets available. The classification of medical images, particularly radiographic images, remains one of the biggest hurdles in medical diagnosis because of the restricted availability of annotated medical images. However, such difficulty can be solved by utilizing several deep learning strategies, including data augmentation and transfer learning. The aim was to build a model that would detect abnormalities in chest x-ray images with the highest probability. To do that, different models were built with different features. While making a CNN model, one of the main tasks is to tune the model by changing the hyperparameters and layers so that the model gives out good training and testing results. In our case, three different models were built, and finally, the last one gave out the best-predicted results. From that last model, we got 98% training accuracy, 84% validation, and 81% testing accuracy. The reason behind the final model giving out the best evaluation scores is that it was a well-fitted model. There was no overfitting or underfitting issues. Our aim with this project was to make a tool using the CNN model in R language, which will help detect abnormalities in radiography images. The tool will be able to detect diseases such as Pneumonia, Covid-19, Effusions, Infiltration, Pneumothorax, and others. Because of its high accuracy, this research chose to use supervised multi-class classification techniques as well as Convolutional Neural Networks (CNNs) to classify different chest x-ray images. CNNs are extremely efficient and successful at reducing the number of parameters while maintaining the quality of the primary model. CNNs are also trained to recognize the edges of various objects in any batch of images. CNNs automatically discover the relevant aspects in labeled data and learn the distinguishing features for each class by themselves.

Single Tooth Segmentation on Panoramic X-Rays Using End-to-End Deep Neural Networks

In dentistry, panoramic X-ray images are extensively used by dentists for tooth structure analysis and disease diagnosis. However, the manual analysis of these images is time-consuming and prone to misdiagnosis or overlooked. While deep learning techniques have been employed to segment teeth in panoramic X-ray images, accurate segmentation of individual teeth remains an underexplored area. In this study, we propose an end-to-end deep learning method that effectively addresses this challenge by employing an improved combinatorial loss function to separate the boundaries of adjacent teeth, enabling precise segmentation of individual teeth in panoramic X-ray images. We validate the feasibility of our approach using a challenging dataset. By training our segmentation network on 115 panoramic X-ray images, we achieve an intersection over union (IoU) of 86.56% for tooth segmentation and an accuracy of 65.52% in tooth counting on 87 test set images. Experimental results demonstrate the significant improvement of our proposed method in single tooth segmentation compared to existing methods.

Intelligent extraction of road cracks based on vehicle laser point cloud and panoramic sequence images

In light of the limited efficacy of conventional methods for identifying pavement cracks and the absence of comprehensive depth and location data in two-dimensional photographs,this study presents an intelligent strategy for extracting road cracks.This methodology involves the integration of laser point cloud data obtained from a vehicle-mounted system and a panoramic sequence of images.The study employs a vehicle-mounted LiDAR measurement system to acquire laser point cloud and panoramic sequence image data simultaneously.A convolutional neural network is utilized to extract cracks from the panoramic sequence image.The extracted sequence image is then aligned with the laser point cloud,enabling the assignment of RGB information to the vehicle-mounted three dimensional(3D)point cloud and location information to the two dimensional(2D)panoramic image.Additionally,a threshold value is set based on the crack elevation change to extract the aligned roadway point cloud.The three-dimensional data pertaining to the cracks can be acquired.The experimental findings demonstrate that the use of convolutional neural networks has yielded noteworthy outcomes in the extraction of road cracks.The utilization of point cloud and image alignment techniques enables the extraction of precise location data pertaining to road cracks.This approach exhibits superior accuracy when compared to conventional methods.Moreover,it facilitates rapid and accurate identification and localization of road cracks,thereby playing a crucial role in ensuring road maintenance and traffic safety.Consequently,this technique finds extensive application in the domains of intelligent transportation and urbanization development.The technology exhibits significant promise for use in the domains of intelligent transportation and city development.

Resolution analysis of thermal neutron radiography based on accelerator-driven compact neutron source

Owing to the immobility of traditional reactors and spallation neutron sources,the demand for compact thermal neutron radiography(CTNR)based on accelerator neutron sources has rapidly increased in industrial applications.Recently,thermal neutron radiography experiments based on a D-T neutron generator performed by Hefei Institutes of Physical Science indicated a significant resolution deviation between the experimental results and the values calculated using the traditional resolution model.The experimental result was up to 23%lower than the calculated result,which hinders the achievement of the design goal of a compact neutron radiography system.A GEANT4 Monte Carlo code was developed to simulate the CTNR process,aiming to identify the key factors leading to resolution deviation.The effects of a low collimation ratio and high-energy neutrons were analyzed based on the neutron beam environment of the CTNR system.The results showed that the deviation was primarily caused by geometric distortion at low collimation ratios and radiation noise induced by highenergy neutrons.Additionally,the theoretical model was modified by considering the imaging position and radiation noise factors.The modified theoretical model was in good agreement with the experimental results,and the maximum deviation was reduced to 4.22%.This can be useful for the high-precision design of CTNR systems.

Geographical Information Visualization on a Panoramic Sphere in an Immersive Environment

In this paper,we propose a novel approach to visualizing global geographical information:a panoramic sphere in an immersive environment.The whole geographical surface can be observed through the rotating of heads as the viewpoint of the panoramic sphere is inside the sphere.We compared three approaches to visualizing the earth for rendering the geographical information in a virtual reality environment.On the tasks of terrestrial and marine geographical information,we compare the visualization effects on a)a globe,b)a flat map and c)a panoramic sphere.Terrestrial geographical information tasks include the area comparison and direction determination.Marine geographical information tasks contain the visualization of sea surface temperature and sea surface currents.For terrestrial geographical information tasks,the experimental results show that the panoramic sphere outperforms the globe and the flat map,with a higher average accuracy and a shorter time.On marine geographical information task,the panoramic sphere visualization is also superior to the flat map and the globe in an immersive environment for the sea surface temperature data and the sea surface current fields.In all three visualization experiments,the panoramic sphere is most preferred by the participants,particularly for global,transcontinental and transoceanic needs.

Transfer learning-based super-resolution in panoramic models for predicting mandibular third molar extraction difficulty: a multi-center study

Background:This study aims to predict the extraction difficulty of mandibular third molars based on panoramic images using transfer learning while employing super-resolution(SR)technology to enhance the feasibility and validity of the prediction.Methods:We reviewed a total of 608 preoperative mandibular third molar panoramic radiographs from two medical facilities:the First Affiliated Hospital of Zhengzhou University(n=509;456 in the training set and 53 in the test set)and the Henan Provincial Dental Hospital(n=99 in the validation set).We conducted a deep-transfer learning network on high-resolution(HR)panoramic radiographs to improve the longitudinal resolution of the images and obtained the SR images.Subsequently,we constructed models named Model-HR and Model-SR using high-dimensional quantitative features extracted through the Least Absolute Shrinkage and Selection Operator method.The models’performances were evaluated using the receiver operating characteristic curve(ROC).To assess the reliability of the model,we compared the results from the test set with those of three dentists.Results:Model-SR outperformed Model-HR(area under the curve(AUC):0.779,sensitivity:85.5%,specificity:60.9%,and accuracy:79.8%vs.AUC:0.753,sensitivity:73.7%,specificity:73.9%,and accuracy:73.7%)in predicting the difficulty of extracting mandibular third molars.Both Model-HR(AUC=0.821,95%CI 0.687–0.956)and Model-SR(AUC=0.963,95%CI 0.921–0.999)demonstrated superior performance compared to expert dentists(highest AUC=0.799,95%CI 0.671–0.927).Conclusions:Model-SR yielded superior predictive performance in determining the difficulty of extracting mandibular third molars when compared with Model-HR and expert dentists’visual assessments.

In situ study on columnar-equiaxed transition and anaxial columnar dendrite growth of Al-15%Cu alloy by synchrotron radiography

Directional solidification of Al-15% （mass fraction） Cu alloy was investigated by in situ and real time radiography which was performed by Shanghai synchrotron radiation facility （SSRF）. The imaging results reveal that columnar to equiaxed transition （CET） is provoked by external thermal disturbance. The detaching and floating of fragments of dendrite arms are the prelude of the transition when the solute boundary layer in front of the solid-liquid interface is thin. And the dendrite triangular tip is the fracture sensitive zone. When the conditions are suitable, new dendrites can sprout and grow up. This kind of dendrite has no obvious stem and is named anaxial columnar dendrites.

Development of Brief Image Quality Evaluation Criteria for Digital OrthoPantomography （OPG） Images in Dental Radiography

An OPG （orthopantmography） is an extra-oral radiographic imaging method which provides a panoramic or wide view of both jaws and teeth on a single image. Digital OPG images provide high contrast with more details of the dentitions. The research main objective was to produce sophisticated and effective criteria that can be used by any radiographer with sound knowledge to identify common errors of digital OPG images and to increase the concern of high frequency of errors to minimize them to give an optimum image quality. The study was designed as retrospective cross sectional study. Hundred digital OPG images are evaluated by three qualified radiographers who had dental radiography experience and four student radiographers. Paired t-test was used to see the difference between the responses of radiographers and student radiographers. Kruskal-Wallis Test was used to see difference between each evaluator. Possible errors of OPG were divided into four main categories （identification, artifact, anatomical coverage and patient positioning）. Each main category consists of sub-categories. Values of subcategories were given according to their importance to get the total of 100% for each main category. The results showed that there is no significant difference between radiographers and student radiographers’ responses and also between each evaluator. Hence it shows that the criteria were an easy understandable and user-friendly tool. And results showed the frequent error category was loss of anatomical coverage and frequent error was absence of positioning the tongue against the palate.

Evaluation of an asymptomatic COVID-19 patient post-surgery with chest radiography: A surgeon’s dilemma

Routine chest radiography is not a requirement in post-surgery cardiac bypass patients.However,the safety of abandoning routine chest radiographs in critically ill patients remains uncertain.Surgery in an asymptomatic coronavirus disease 2019(COVID-19)patient presents additional challenges in postoperative management.Chest radiography remains a valuable tool for assessment of all patients,even a stable one.Management of surgical patients as an emergency in an asymptomatic COVID-19 case remains a surgeon’s dilemma.

Contrast sensitivity in 14 MeV fast neutron radiography

Fast neutron radiography(FNR) is an effective non-destructive testing technique.Due to the scattering effect and low detection efficiency,the detection limit of FNR under certain conditions cannot be determined.In order to obtain the minimum detectable thickness by FNR,we studied the contrast sensitivity of FNR lead samples,both theoretically and experimentally.We then clarified the relationship between pixel value and irradiation time,and sample materials and thickness.Our experiment,using a4-cm-thick lead sample,verified our theoretical expression of FNR contrast sensitivity.

Digital radiography of crush thoracic trauma in the Sichuan earthquake

AIM:To investigate the features of crush thoracic trauma in Sichuan earthquake victims using chest digital radiography(CDR).METHODS:We retrospectively reviewed 772 CDR of 417 females and 355 males who had suffered crush thoracic trauma in the Sichuan earthquake.Patient age ranged from 0.5 to 103 years.CDR was performed between May 12,2008 and June 7,2008.We looked for injury to the thoracic cage,pulmonary parenchyma and the pleura.obtained in 349 patients,the remaining 423 patients underwent only AP CDR.Thoracic cage fractures,pulmonary contusion and pleural injuries were noted in 331(42.9%;95% CI:39.4%-46.4%),67 and 135 patients,respectively.Of the 256 patients with rib fractures,the mean number of fractured ribs per patient was 3.Rib fractures were mostly distributed from the 3rd through to the 8th ribs and the vast majority involved posterior and lateral locations along the rib.Rib fractures had a significant positive association with non-rib thoracic fractures,pulmonary contusion and pleural injuries(P < 0.001).The number of rib fractures and pulmonary contusions were significant factors associated with patient death.CONCLUSION:Earthquake-related crush thoracic trauma has the potential for multiple fractures.The high number of fractured ribs and pulmonary contusions were significant factors which needed appropriate medical treatment.

Comparison of conventional radiography and MDCT in suspected scaphoid fractures

AIM: To determine the diagnostic accuracy and radiation dose of conventional radiography and multidetector computed tomography(MDCT) in suspected scaphoid fractures.METHODS: One hundred twenty-four consecutive patients were enrolled in our study who had suffered from a wrist trauma and showed typical clinical symptoms suspicious of an acute scaphoid fracture. All patients had initially undergone conventional radiography. Subsequent MDCT was performed within 10 d because of persisting clinical symptoms. Using the MDCT data as the reference standard, a fourfold table was used to classify the test results. The effective dose and impaired energy were assessed in order to compare the radiation burden of the two techniques. The Wilcoxon test was performed to compare the two diagnostic modalities.RESULTS: Conventional radiography showed 34 acute fractures of the scaphoid in 124 patients(42.2%). Subsequent MDCT revealed a total of 42 scaphoid fractures. The sensitivity of conventional radiography for scaphoid fracture detection was 42.8% and its specificity was 80% resulting in an overall accuracy of 59.6%. Conventional radiography was significantly inferior to MDCT(P < 0.01) concerning scaphoidfracture detection. The mean effective dose of MDCT was 0.1 m Sv compared to 0.002 m Sv of conventional radiography.CONCLUSION: Conventional radiography is insufficient for accurate scaphoid fracture detection. Regarding the almost negligible effective dose, MDCT should serve as the first imaging modality in wrist trauma.

Imaging internal density structure of the Laoheishan volcanic cone with cosmic ray muon radiography

Muon radiography is a promising technique for imaging the internal density structures of targets such as tunnels,pyramids,and volcanoes up to a scale of a few hundred meters by measuring the flux attenuation of cosmic ray muons after they have traveled through these targets.In this study,we conducted experimental muon radiography of one of the volcanoes in the Wudalianchi area in Northeast China to image its internal density structure.The muon detector used in this study was composed of plastic scintillators and silicon photomultipliers.After approximately one and a half months of observing the crater and conduit of the Laoheishan volcano cone in Wudalianchi from September 23^(rd) to November 10^(th) 2019,more than 3 million muon tracks fulfilling the data selection criteria were collected.Based on the muon samples and high-resolution topography obtained through aerial photogrammetry using an unmanned aerial vehicle,a density image of the Laoheishan volcano cone was constructed.The results obtained in this experiment demonstrate the feasibility of using a radiography technique based on plastic scintillator detectors.To obtain the density distribution,we performed a detailed background analysis and found that low-energy charged particles dominated the background noise.Relatively higher densities were found near the surface of the volcanic cone,whereas relatively lower densities were found near the center of the volcanic cone.The experiment in this study is the first volcano muon tomography study performed in China.Our work provides an important reference for future research.

Monte Carlo simulation for bremsstrahlung and photoneutron yields in high-energy x-ray radiography

This paper reports on the results of calculations using a Monte Carlo code （MCNP5） to study the properties of photons, electrons and photoneutrons obtained in the converted target and their transportations in x-ray radiography. A comparison between measurements and calculations for bremsstrahlung and photoneutrons is presented. The radiographic rule and the effect of the collimator on the image are studied with the experimental model. The results provide exact parameters for the optimal design of radiographic layout and shielding systems.

A race to uncover a panoramic view of primary liver cancer

Introduction Primary liver cancer, the second most common cause of cancer related death worldwide, presents ethnic, etiological, sex, and geographical diversity2 （Figure 1A）. At the histological level, liver cancer includes two major types： hepatocellular carcinoma （HCC, about 80%） and cholangiocarcinoma （CCA, about 15%）. Many etiological factors contribute to HCC development, such as hepatitis B virus （HBV）, hepatitis C virus （HCV）, aflatoxin B1 （AFB1）, alcohol, and metabolic diseases3. By contrast, the major risk factors for CCA are liver flukes （Opisthorchis viverrini and Clonorchis sinensis） and primary sclerosing cholangitis4,

Areal density and spatial resolution of high energy electron radiography

Ultrafast imaging tools are of great importance for determining the dynamic density distribution in high energy density(HED)matter.In this work,we designed a high energy electron radiography(HEER)system based on a linear electron accelerator to evaluate its capability for imaging HED matter.40 MeV electron beams were used to image an aluminum target to study the density resolution and spatial resolution of HEER.The results demonstrate a spatial resolution of tens of micrometers.The interaction of the beams with the target and the beam transport of the transmitted electrons are further simulated with EGS5 and PARMELA codes,with the results showing good agreement with the experimental resolution.Furthermore,the experiment can be improved by adding an aperture at the Fourier plane.

Proton radiography of magnetic fields generated with an open-ended coil driven by high power laser pulses

Recently generation of strong magnetic(B)fields has been demonstrated in capacitor coils heated by high power laser pulses[S.Fujioka et al.,Sci.Rep.3,1170(2013)].This paper will present a direct measurement of B field generated with an open-ended coil target driven by a nanosecond laser pulse using ultrafast proton radiography.The radiographs are analyzed with particle-tracing simulations.The B field at the coil center is inferred to be ~50 T at an irradiance of ~5×10^(14) W·cm^(-2).The B field generation is attributed to the background cold electron flow pointing to the laser focal spot,where a target potential is induced due to the escape of energetic electrons.

Effectiveness of chest radiography,lung ultrasound and thoracic computed tomography in the diagnosis of congestive heart failure

Hydrostatic pulmonary edema is as an abnormal in-crease in extravascular water secondary to elevatedpressure in the pulmonary circulation, due to conges-tive heart failure or intravascular volume overload.Diagnosis of hydrostatic pulmonary edema is usuallybased on clinical signs associated to conventional ra-diography findings. Interpretation of radiologic signsof cardiogenic pulmonary edema are often question-able and subject. For a bedside prompt evaluation,lung ultrasound(LUS) may assess pulmonary conges-tion through the evaluation of vertical reverberationartifacts, known as B-lines. These artifacts are relatedto multiple minimal acoustic interfaces between smallwater-rich structures and alveolar air, as it happens incase of thickened interlobular septa due to increase of extravascular lung water. The number, diffusion and in-tensity of B lines correlates with both the radiologic andinvasive estimate of extravascular lung water. The inte-gration of conventional chest radiograph with LUS canbe very helpful to obtain the correct diagnosis. Com-puted tomography(CT) is of limited use in the work upof cardiogenic pulmonary edema, due to its high cost,little use in the emergencies and radiation exposure.However, a deep knowledge of CT signs of pulmonaryedema is crucial when other similar pulmonary condi-tions may occasionally be in the differential diagnosis.