Objective:To analyze the value of multi-slice spiral computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of carpal joint injury.Methods:A total of 130 patients with suspected wrist injuries admi...Objective:To analyze the value of multi-slice spiral computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of carpal joint injury.Methods:A total of 130 patients with suspected wrist injuries admitted to the Department of Orthopedics of our hospital from January 2023 to January 2024 were selected and randomly divided into a single group(n=65)and a joint group(n=65).The single group was diagnosed using multi-slice spiral CT,and the joint group was diagnosed using multi-slice spiral CT and magnetic resonance imaging,with pathological diagnosis as the gold standard.The diagnostic results of both groups were compared to the gold standard,and the diagnostic energy efficiency of both groups was compared.Results:The diagnostic results of the single group compared with the gold standard were significant(P<0.05).The diagnostic results of the joint group compared with the gold standard were not significant(P>0.05).The sensitivity and accuracy of diagnosis in the joint group were significantly higher than that in the single group(P<0.05).The specificity of diagnosis in the joint group was higher as compared to that in the single group(P>0.05).Conclusion:The combination of multi-slice spiral CT and MRI was highly accurate in diagnosing wrist injuries,and the misdiagnosis rate and leakage rate were relatively low.Hence,this diagnostic program is recommended to be popularized.展开更多
Utilizing lightweight Al alloys in various industrial applications requires achieving precise pressure tightness and leak requirements.Vacuum pressure impregnation(VPI)with thermosetting polymers is commonly used to a...Utilizing lightweight Al alloys in various industrial applications requires achieving precise pressure tightness and leak requirements.Vacuum pressure impregnation(VPI)with thermosetting polymers is commonly used to address leakage defects in die-cast Al alloys.In this study,the efficacy of the VPI technique in sealing alloy parts was investigated using a combination of nondestructive micro X-ray computed tomography(micro XCT)and a standard leak test.The results demonstrate that the commonly used water leak test is insufficient for determining the sealing performance.Instead,micro XCT shows distinct advantages by enabling more comprehensive analysis.It reveals the presence of a low atomic number impregnates sealant within casting defects,which has low grey contrast and allows for visualizing primary leakage paths in 3D.The effective atomic number of impregnated resin is 6.75 and that of Al alloy is 13.69 by dual-energy X-ray CT.This research findings will contribute to enhancing the standard VPI process parameters and the properties of impregnating sealants to improve quality assurance for impregnation in industrial metals.展开更多
Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL...Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.展开更多
Objective: To evaluate the lung CT scan as a possible predictive diagnostic method for COVID-19 in the Cameroonian context. Methods: We designed a cross sectional study. Suspected cases of COVID-19 during the first wa...Objective: To evaluate the lung CT scan as a possible predictive diagnostic method for COVID-19 in the Cameroonian context. Methods: We designed a cross sectional study. Suspected cases of COVID-19 during the first wave at the national social insurance fund (NSIF) hospital were screened with both COVID-19 with lung CT scan and a PCR test. Univariate analysis was performed for sample description and multivariate analysis to assess the correlation between positive results for the PCR and other parameters. We estimated the optimum threshold of sensitivity/specificity, and area under curve using the empirical method and package. Results: A total of 62 suspected COVID-19 cases were recorded, predominantly males (Sex Ratio = 2.2) with a median age of 58.5 (IQR = 19.7). Among our 62 patients, 29 (46.8%) were confirmed COVID-19 cases with positive PCR results. All the patients had a thorax CT scan with a median impairment of 40% (IQR = 20%). The optimum threshold estimate for CT scan for COVID-19 infection diagnosis was 60% (95% CI = 25% - 80%). Overall, the sensitivity and specificity estimates were 0.30 (95% CI = 0.15 - 0.49) and 0.87 (95% CI = 0.70 - 0.96), respectively, leading to an Area Under Curve (AUC) estimate of 0.59 (95% CI = 0.46, 0.71). Conclusion: In this setting, lung CT scan was neither sensitive nor specific to predict COVID-19 disease.展开更多
Background: The plain abdominal x-ray is one of the commonly requested investigations in the children emergency room, paediatric surgical ward and neonatal wards. The short interval required to carry out this investig...Background: The plain abdominal x-ray is one of the commonly requested investigations in the children emergency room, paediatric surgical ward and neonatal wards. The short interval required to carry out this investigative procedure and obtain results makes it the first imaging modality used to unravel the different causes of acute abdominal conditions in children. The safety of abdominal x-ray in children makes it attractive for use in paediatric surgical practice as part of routine work-up for undifferentiated acute abdominal conditions and also to diagnose specific causes of acute abdomen in children. Setting: Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State. Objectives: Evaluation of the role of plain abdominal x-ray in diagnosing common acute abdominal conditions in children. Materials and method: Patients admitted to the children emergency room, paediatric surgical wards, children’s ward and neonatal ward who had plain abdominal x-ray as part of their diagnostic work-up were included in the study. They were studied prospectively between March 2011 and April 2021. Results: Three Hundred and Ninety-nine patients who had plain abdominal x-rays as part of their diagnostic work-up were studied. Males were 240 while females were 159, a male to female ratio of 1.5:1. The patients were aged between 1 day to 16 years. Differential diagnoses made with plain abdominal x-ray were intestinal obstruction in 298, perforated viscus 69 patients, intra-abdominal masses 13 patients and location of intra-abdominal foreign body 14. Intestinal obstruction cases in which plain abdominal x-ray played a role in their diagnosis and management included the following: intussusception 66, neonatal sepsis 60, malrotation 48, intestinal atresia 42, anorectal malformation 32, hirschsprung’s disease in 30 cases, pyloric stenosis 24, obstructed hernia 22, post-operative adhesions 16 and intestinal helminthiasis 12. Perforated viscus accounted for 69 indications. Out of these indications, perforated gut in intussusception 19, perforated typhoid ileitis was responsible in 13 cases, gut perforation in blunt abdominal trauma 8, perforation in strangulated hernia 11 cases, perforated gut in malrotation 7, ceacal perforation in hirschsprugs disease 6 and colonic perforation in necrotizing enterocolitis 5 cases. Conclusion: Plain abdominal x-ray remains a role to play in the differential diagnosis and management of common paediatric acute abdominal conditions.展开更多
The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,whi...The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.展开更多
文摘Objective:To analyze the value of multi-slice spiral computed tomography(CT)and magnetic resonance imaging(MRI)in the diagnosis of carpal joint injury.Methods:A total of 130 patients with suspected wrist injuries admitted to the Department of Orthopedics of our hospital from January 2023 to January 2024 were selected and randomly divided into a single group(n=65)and a joint group(n=65).The single group was diagnosed using multi-slice spiral CT,and the joint group was diagnosed using multi-slice spiral CT and magnetic resonance imaging,with pathological diagnosis as the gold standard.The diagnostic results of both groups were compared to the gold standard,and the diagnostic energy efficiency of both groups was compared.Results:The diagnostic results of the single group compared with the gold standard were significant(P<0.05).The diagnostic results of the joint group compared with the gold standard were not significant(P>0.05).The sensitivity and accuracy of diagnosis in the joint group were significantly higher than that in the single group(P<0.05).The specificity of diagnosis in the joint group was higher as compared to that in the single group(P>0.05).Conclusion:The combination of multi-slice spiral CT and MRI was highly accurate in diagnosing wrist injuries,and the misdiagnosis rate and leakage rate were relatively low.Hence,this diagnostic program is recommended to be popularized.
文摘Utilizing lightweight Al alloys in various industrial applications requires achieving precise pressure tightness and leak requirements.Vacuum pressure impregnation(VPI)with thermosetting polymers is commonly used to address leakage defects in die-cast Al alloys.In this study,the efficacy of the VPI technique in sealing alloy parts was investigated using a combination of nondestructive micro X-ray computed tomography(micro XCT)and a standard leak test.The results demonstrate that the commonly used water leak test is insufficient for determining the sealing performance.Instead,micro XCT shows distinct advantages by enabling more comprehensive analysis.It reveals the presence of a low atomic number impregnates sealant within casting defects,which has low grey contrast and allows for visualizing primary leakage paths in 3D.The effective atomic number of impregnated resin is 6.75 and that of Al alloy is 13.69 by dual-energy X-ray CT.This research findings will contribute to enhancing the standard VPI process parameters and the properties of impregnating sealants to improve quality assurance for impregnation in industrial metals.
基金supported by the National Natural Science Foundation of China(Grant Nos.41877267 and 41877260)the Priority Research Program of the Chinese Academy of Sciences(Grant No.XDA13010201).
文摘Different sedimentary zones in coral reefs lead to significant anisotropy in the pore structure of coral reef limestone(CRL),making it difficult to study mechanical behaviors.With X-ray computed tomography(CT),112 CRL samples were utilized for training the support vector machine(SVM)-,random forest(RF)-,and back propagation neural network(BPNN)-based models,respectively.Simultaneously,the machine learning model was embedded into genetic algorithm(GA)for parameter optimization to effectively predict uniaxial compressive strength(UCS)of CRL.Results indicate that the BPNN model with five hidden layers presents the best training effect in the data set of CRL.The SVM-based model shows a tendency to overfitting in the training set and poor generalization ability in the testing set.The RF-based model is suitable for training CRL samples with large data.Analysis of Pearson correlation coefficient matrix and the percentage increment method of performance metrics shows that the dry density,pore structure,and porosity of CRL are strongly correlated to UCS.However,the P-wave velocity is almost uncorrelated to the UCS,which is significantly distinct from the law for homogenous geomaterials.In addition,the pore tensor proposed in this paper can effectively reflect the pore structure of coral framework limestone(CFL)and coral boulder limestone(CBL),realizing the quantitative characterization of the heterogeneity and anisotropy of pore.The pore tensor provides a feasible idea to establish the relationship between pore structure and mechanical behavior of CRL.
文摘Objective: To evaluate the lung CT scan as a possible predictive diagnostic method for COVID-19 in the Cameroonian context. Methods: We designed a cross sectional study. Suspected cases of COVID-19 during the first wave at the national social insurance fund (NSIF) hospital were screened with both COVID-19 with lung CT scan and a PCR test. Univariate analysis was performed for sample description and multivariate analysis to assess the correlation between positive results for the PCR and other parameters. We estimated the optimum threshold of sensitivity/specificity, and area under curve using the empirical method and package. Results: A total of 62 suspected COVID-19 cases were recorded, predominantly males (Sex Ratio = 2.2) with a median age of 58.5 (IQR = 19.7). Among our 62 patients, 29 (46.8%) were confirmed COVID-19 cases with positive PCR results. All the patients had a thorax CT scan with a median impairment of 40% (IQR = 20%). The optimum threshold estimate for CT scan for COVID-19 infection diagnosis was 60% (95% CI = 25% - 80%). Overall, the sensitivity and specificity estimates were 0.30 (95% CI = 0.15 - 0.49) and 0.87 (95% CI = 0.70 - 0.96), respectively, leading to an Area Under Curve (AUC) estimate of 0.59 (95% CI = 0.46, 0.71). Conclusion: In this setting, lung CT scan was neither sensitive nor specific to predict COVID-19 disease.
文摘Background: The plain abdominal x-ray is one of the commonly requested investigations in the children emergency room, paediatric surgical ward and neonatal wards. The short interval required to carry out this investigative procedure and obtain results makes it the first imaging modality used to unravel the different causes of acute abdominal conditions in children. The safety of abdominal x-ray in children makes it attractive for use in paediatric surgical practice as part of routine work-up for undifferentiated acute abdominal conditions and also to diagnose specific causes of acute abdomen in children. Setting: Olabisi Onabanjo University Teaching Hospital, Sagamu, Ogun State. Objectives: Evaluation of the role of plain abdominal x-ray in diagnosing common acute abdominal conditions in children. Materials and method: Patients admitted to the children emergency room, paediatric surgical wards, children’s ward and neonatal ward who had plain abdominal x-ray as part of their diagnostic work-up were included in the study. They were studied prospectively between March 2011 and April 2021. Results: Three Hundred and Ninety-nine patients who had plain abdominal x-rays as part of their diagnostic work-up were studied. Males were 240 while females were 159, a male to female ratio of 1.5:1. The patients were aged between 1 day to 16 years. Differential diagnoses made with plain abdominal x-ray were intestinal obstruction in 298, perforated viscus 69 patients, intra-abdominal masses 13 patients and location of intra-abdominal foreign body 14. Intestinal obstruction cases in which plain abdominal x-ray played a role in their diagnosis and management included the following: intussusception 66, neonatal sepsis 60, malrotation 48, intestinal atresia 42, anorectal malformation 32, hirschsprung’s disease in 30 cases, pyloric stenosis 24, obstructed hernia 22, post-operative adhesions 16 and intestinal helminthiasis 12. Perforated viscus accounted for 69 indications. Out of these indications, perforated gut in intussusception 19, perforated typhoid ileitis was responsible in 13 cases, gut perforation in blunt abdominal trauma 8, perforation in strangulated hernia 11 cases, perforated gut in malrotation 7, ceacal perforation in hirschsprugs disease 6 and colonic perforation in necrotizing enterocolitis 5 cases. Conclusion: Plain abdominal x-ray remains a role to play in the differential diagnosis and management of common paediatric acute abdominal conditions.
文摘The quick spread of the CoronavirusDisease(COVID-19)infection around the world considered a real danger for global health.The biological structure and symptoms of COVID-19 are similar to other viral chest maladies,which makes it challenging and a big issue to improve approaches for efficient identification of COVID-19 disease.In this study,an automatic prediction of COVID-19 identification is proposed to automatically discriminate between healthy and COVID-19 infected subjects in X-ray images using two successful moderns are traditional machine learning methods(e.g.,artificial neural network(ANN),support vector machine(SVM),linear kernel and radial basis function(RBF),k-nearest neighbor(k-NN),Decision Tree(DT),andCN2 rule inducer techniques)and deep learningmodels(e.g.,MobileNets V2,ResNet50,GoogleNet,DarkNet andXception).A largeX-ray dataset has been created and developed,namely the COVID-19 vs.Normal(400 healthy cases,and 400 COVID cases).To the best of our knowledge,it is currently the largest publicly accessible COVID-19 dataset with the largest number of X-ray images of confirmed COVID-19 infection cases.Based on the results obtained from the experiments,it can be concluded that all the models performed well,deep learning models had achieved the optimum accuracy of 98.8%in ResNet50 model.In comparison,in traditional machine learning techniques, the SVM demonstrated the best result for an accuracy of 95% and RBFaccuracy 94% for the prediction of coronavirus disease 2019.
