X-ray

摘要： Introduction: Cranioencephalic trauma is a frequent reason for admission to emergency departments and is a source of mild to severe neuropsychological defects that will persist over time. Their management remains difficult. Objectives: To evaluate the sequelae presented by patients suffering from cranioencephalic trauma. Methods: This was a retrospective, descriptive, cross-sectional study conducted at the National Hospital of Zinder. It will include all patients admitted and hospitalised in the emergency, intensive care and neurosurgery departments of Zinder National Hospital for head injury over a period of 28 months from 1 January 2016 to 30 April 2018. Brain scan, X-ray were the imaging tests used. Results: Out of a total of 974 admissions, 367 were retained, i.e. 37.6%, with a male predominance (82.6%). The average age was 26.5 years. MVAs were represented in 89.7% of cases. Moderate CTE accounted for 64% of cases. Altered consciousness was reported in 295 patients (80.38% of cases). Brain scans were used in 76.7% of cases and skull X-rays in 4.2% of cases. Medical management was performed in all patients. Treatment was operative in 78 patients (21.25%). Recovery without immediate sequelae was found in 187 patients (50.9%). Persistent headache represented 47.7% of the late sequelae observed in the patients, epileptic seizures represented 16.8% of the late sequelae, neurological deficit represented 14.7%. Conclusion: Cranioencephalic trauma represents a major public health issue. Although their in-hospital management remains a challenge, post-hospital management related to the appearance of sequelae remains another.

摘要： Objective:To explore the performance characteristics of CT examination in primary spontaneous pneumothorax(PSP)and the effect of pleurodesis on patients with PSP.Methods:Sixty-four patients with PSP,who received medical care in the Affiliated Hospital of Hebei University from January 2017 to December 2021,were selected as the research subjects,of which 40 were male and 24 were female patients.All 64 patients were examined by X-ray and CT;the density,enhancement,and morphology of the pneumothorax were observed and analyzed,and the classification of pneumothorax was done.Results:The clinical analysis of 64 patients with PSP showed that the number of cases with unilateral pneumothorax was 42,accounting for 65.63%,whereas the number of cases with bilateral pneumothorax was 22,accounting for 34.37%.Among the cases of unilateral pneumothorax,the number of cases with left pneumothorax was 26,accounting for 61.90%,whereas the proportion of cases with right pneumothorax was 38.10%.When examined by CT,the diagnostic coincidence rate of 64 patients with PSP was 73.44%;using X-ray examination,the diagnostic coincidence rate of 64 patients with PSP was 92.19%.Conclusion:The detection accuracy of CT is higher than that of X-ray examination,which may improve the treatment effect in PSP,ensure the accuracy of findings,and facilitate follow-up treatment as well as the effect of postoperative analysis.

摘要： Progress in the rocket industry is only possible on the basis of new, higher performance and more environmentally friendly materials compared to up-to-date propellant ingredients for liquid, solid, gelled and hybrid propellant systems. In this work, synthetic methods have been developed for the preparation of new energetic azofurazans bearing nitroxymethyl or azidomethyl groups. All prepared compounds were fully characterized by multinuclear NMR and IR spectroscopies, as well as elemental analyses. An analysis of the structural features based on the X-ray single-crystal diffraction made it possible to discuss their influence on the densities of the azofurazans of this study. Thermal decomposition and combustion of nitroxymethyl and azidomethyl azofurazans were studied using a number of complementary experimental techniques, namely thermogravimetry, differential scanning calorimetry, manometry, microthermocouple measurements in the combustion wave. The structural and physical characteristics of these new energetic analogues illustrate the extent to which the nature of the explosophoric groups can be used to tune the performace of the azofurazan framework. These azofurazans possess positive calculated enthalpy of formation and are promising candidates for new environmentally friendly energetic materials.

摘要： Corona is a viral disease that has taken the form of an epidemic and is causing havoc worldwide after its first appearance in the Wuhan state of China in December 2019.Due to the similarity in initial symptoms with viral fever,it is challenging to identify this virus initially.Non-detection of this virus at the early stage results in the death of the patient.Developing and densely populated countries face a scarcity of resources like hospitals,ventilators,oxygen,and healthcare workers.Technologies like the Internet of Things(IoT)and artificial intelligence can play a vital role in diagnosing the COVID-19 virus at an early stage.To minimize the spread of the pandemic,IoT-enabled devices can be used to collect patient’s data remotely in a secure manner.Collected data can be analyzed through a deep learning model to detect the presence of the COVID-19 virus.In this work,the authors have proposed a three-phase model to diagnose covid-19 by incorporating a chatbot,IoT,and deep learning technology.In phase one,an artificially assisted chatbot can guide an individual by asking about some common symptoms.In case of detection of even a single sign,the second phase of diagnosis can be considered,consisting of using a thermal scanner and pulse oximeter.In case of high temperature and low oxygen saturation levels,the third phase of diagnosis will be recommended,where chest radiography images can be analyzed through an AI-based model to diagnose the presence of the COVID-19 virus in the human body.The proposed model reduces human intervention through chatbot-based initial screening,sensor-based IoT devices,and deep learning-based X-ray analysis.It also helps in reducing the mortality rate by detecting the presence of the COVID-19 virus at an early stage.

摘要： This research article proposes an automatic frame work for detectingCOVID -19 at the early stage using chest X-ray image. It is an undeniable factthat coronovirus is a serious disease but the early detection of the virus presentin human bodies can save lives. In recent times, there are so many research solutions that have been presented for early detection, but there is still a lack in needof right and even rich technology for its early detection. The proposed deeplearning model analysis the pixels of every image and adjudges the presence ofvirus. The classifier is designed in such a way so that, it automatically detectsthe virus present in lungs using chest image. This approach uses an imagetexture analysis technique called granulometric mathematical model. Selectedfeatures are heuristically processed for optimization using novel multi scaling deep learning called light weight residual–atrous spatial pyramid pooling(LightRES-ASPP-Unet) Unet model. The proposed deep LightRES-ASPPUnet technique has a higher level of contracting solution by extracting majorlevel of image features. Moreover, the corona virus has been detected usinghigh resolution output. In the framework, atrous spatial pyramid pooling(ASPP) method is employed at its bottom level for incorporating the deepmulti scale features in to the discriminative mode. The architectural workingstarts from the selecting the features from the image using granulometricmathematical model and the selected features are optimized using LightRESASPP-Unet. ASPP in the analysis of images has performed better than theexisting Unet model. The proposed algorithm has achieved 99.6% of accuracyin detecting the virus at its early stage.

摘要： COVID-19 has been considered one of the recent epidemics that occurred at the last of 2019 and the beginning of 2020 that world widespread.This spread of COVID-19 requires a fast technique for diagnosis to make the appropriate decision for the treatment.X-ray images are one of the most classifiable images that are used widely in diagnosing patients’data depending on radiographs due to their structures and tissues that could be classified.Convolutional Neural Networks(CNN)is the most accurate classification technique used to diagnose COVID-19 because of the ability to use a different number of convolutional layers and its high classification accuracy.Classification using CNNs techniques requires a large number of images to learn and obtain satisfactory results.In this paper,we used SqueezNet with a modified output layer to classify X-ray images into three groups:COVID-19,normal,and pneumonia.In this study,we propose a deep learning method with enhance the features of X-ray images collected from Kaggle,Figshare to distinguish between COVID-19,Normal,and Pneumonia infection.In this regard,several techniques were used on the selected image samples which are Unsharp filter,Histogram equal,and Complement image to produce another view of the dataset.The Squeeze Net CNN model has been tested in two scenarios using the 13,437 X-ray images that include 4479 for each type(COVID-19,Normal and Pneumonia).In the first scenario,the model has been tested without any enhancement on the datasets.It achieved an accuracy of 91%.But,in the second scenario,the model was tested using the same previous images after being improved by several techniques and the performance was high at approximately 95%.The conclusion of this study is the used model gives higher accuracy results for enhanced images compared with the accuracy results for the original images.A comparison of the outcomes demonstrated the effectiveness of ourDLmethod for classifying COVID-19 based on enhanced X-ray images.

摘要： In this era of pandemic, the future of healthcare industry has never been more exciting. Artificial intelligence and machine learning (AI & ML) present opportunities to develop solutions that cater for very specific needs within the industry. Deep learning in healthcare had become incredibly powerful for supporting clinics and in transforming patient care in general. Deep learning is increasingly being applied for the detection of clinically important features in the images beyond what can be perceived by the naked human eye. Chest X-ray images are one of the most common clinical method for diagnosing a number of diseases such as pneumonia, lung cancer and many other abnormalities like lesions and fractures. Proper diagnosis of a disease from X-ray images is often challenging task for even expert radiologists and there is a growing need for computerized support systems due to the large amount of information encoded in X-Ray images. The goal of this paper is to develop a lightweight solution to detect 14 different chest conditions from an X ray image. Given an X-ray image as input, our classifier outputs a label vector indicating which of 14 disease classes does the image fall into. Along with the image features, we are also going to use non-image features available in the data such as X-ray view type, age, gender etc. The original study conducted Stanford ML Group is our base line. Original study focuses on predicting 5 diseases. Our aim is to improve upon previous work, expand prediction to 14 diseases and provide insight for future chest radiography research.

摘要： BACKGROUND Primary extra-pancreatic pancreatic-type acinar cell carcinoma(ACC)is a rare malignancy,and has only been reported in the gastrointestinal tract,liver,and lymph nodes until now.Extra-pancreatic pancreatic-type ACC in the perinephric space has not been reported.Herein,we report the first case of ACC in the perinephric space and describe its clinical and imaging features,which should be considered when differentiating perinephric space neoplasms.CASE SUMMARY A 48-year-old man with a 5-year history of hypertension was incidentally found to have an asymptomatic right retroperitoneal mass during a routine health check-up.Laboratory tests were normal.Abdominal computed tomography and magnetic resonance imaging showed an oval hypervascular mass with a central scar and enhanced capsule in the right perinephric space.After surgical resection of the neoplasm,the diagnosis was primary extra-pancreatic pancreatic-type ACC.The patient was alive without recurrence or metastasis during a 15-mo follow-up.CONCLUSION This is the first report of an extra-pancreatic ACC in right perinephric space,which should be considered as a possible diagnosis in perinephric tumors.

摘要： 多孔介质空气轴承作为气浮导轨的关键零部件,其静态特性对导轨性能至关重要.采用有限体积法进行了多孔介质空气轴承静态特性仿真,设计了多孔介质平板试验.采用可压缩Forchheimer方程获得多孔介质的渗透率系数;采用X-ray断层扫描方法分离了多孔介质内部孔隙结构,并将孔隙结构细分获得孔隙度.分析了多孔介质CT三维扫描图像的最小重复单元.基于CFD方法对多孔介质空气轴承静态特性进行了数值模拟,对网格数量无关性进行了验证.结果 表明:通过合理设计多孔介质的形状和大小以及气膜的厚度,空气轴承能够获得较好承载力和静刚度.

摘要： The flow field is a pivotal part to manage the transport of water and gas in proton exchange membrane fuel cell.However,the reported water measurement methods(e.g.,X-ray and electrochemical impedance spectroscopy(EIS))cannot give a comprehensive understanding water distribution in the flow field,resulting in challenges in optimizing the channel design and enhancing fuel cell performance.Therefore,we propose a water measurement method combining the X-ray radiography with EIS to investigate the effect of different operating conditions on the growth law and distribution of liquid water in parallel and serpentine flow fields.The attenuation coefficient of liquid water to X-ray is calibrated with constant tube-current and tubevoltage of X-ray generator.Besides,the parallel flow field with hydrophobic treatment is studied.The results show that the water accumulation of the parallel flow field is far more than the serpentine flow field,and the water content of the middle region is higher than that of other regions in the parallel flow field.Furthermore,operating conditions(cathode inlet gas flow rate,inlet gas humidity,and back pressure)have little effect on the liquid water content of the middle region in the parallel flow field.The polarization curve,EIS result,and X-ray radiography show that the performance and water drainage capacity of the hydrophobic parallel flow field are better than the normal one.

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过对工作经验的总结和相关参考文献的学习，本文主要阐述利用X-RAY，ICT和侧面观察放大镜对BGA/CSP器件焊后检查。利用生产中发生的实例，描述BGA/CSP器件诸如短路/空焊/少锡球/锡膏少印等缺陷的判断方法和产生原因。

摘要： 通过CP-MAS C-NMR和X-ray衍射分析了麦草纤维在甲酸体系中的水解过程,结果表明甲酸体系能有效的渗透到麦草纤维内部,使结晶区和非结晶区同时水解。同时也研究了麦草纤维甲酸体系中的水解动力学, 探讨了甲酸体系中盐酸浓度、固液比、反应温度、反应时间对麦草纤维水解的影响以及在该体系中葡萄糖的降解情况。分析了在该体系中葡萄糖的降解情况,结果表明葡萄糖的降解反应和纤维素的水解反应相比是个快反应。麦草纤维素在4％盐酸、甲酸体系中的水解速率60、65、70和75°C时分别为0.0190h、0.0325h、0.0683h和0.0931h;但甲酸体系中葡萄糖也会发生一定的降解,在60、65、70和75°C时其速率分别为0.0285h、0.0448h、0.1098h和0.1436h。麦草纤维水解和葡萄糖降解的Arrhenius方程指前因子分别为:9.121014h和7.08×1015h。麦草纤维水解和葡萄糖降解的表观活化能分别为:106.35kJ/mol和111.00kJ/mol。因此,如何进一步抑制葡萄糖的水解,提高纤维素水解生成葡萄糖的效率仍值得进一步的研究。

摘要： 通过CP-MAS C-NMR和X-ray衍射分析了麦草纤维在甲酸体系中的水解过程,结果表明甲酸体系能有效的渗透到麦草纤维内部,使结晶区和非结晶区同时水解。同时也研究了麦草纤维甲酸体系中的水解动力学, 探讨了甲酸体系中盐酸浓度、固液比、反应温度、反应时间对麦草纤维水解的影响以及在该体系中葡萄糖的降解情况。分析了在该体系中葡萄糖的降解情况,结果表明葡萄糖的降解反应和纤维素的水解反应相比是个快反应。麦草纤维素在4％盐酸、甲酸体系中的水解速率60、65、70和75°C时分别为0.0190h、0.0325h、0.0683h和0.0931h;但甲酸体系中葡萄糖也会发生一定的降解,在60、65、70和75°C时其速率分别为0.0285h、0.0448h、0.1098h和0.1436h。麦草纤维水解和葡萄糖降解的Arrhenius方程指前因子分别为:9.121014h和7.08×1015h。麦草纤维水解和葡萄糖降解的表观活化能分别为:106.35kJ/mol和111.00kJ/mol。因此,如何进一步抑制葡萄糖的水解,提高纤维素水解生成葡萄糖的效率仍值得进一步的研究。

摘要： 通过CP-MAS C-NMR和X-ray衍射分析了麦草纤维在甲酸体系中的水解过程,结果表明甲酸体系能有效的渗透到麦草纤维内部,使结晶区和非结晶区同时水解。同时也研究了麦草纤维甲酸体系中的水解动力学, 探讨了甲酸体系中盐酸浓度、固液比、反应温度、反应时间对麦草纤维水解的影响以及在该体系中葡萄糖的降解情况。分析了在该体系中葡萄糖的降解情况,结果表明葡萄糖的降解反应和纤维素的水解反应相比是个快反应。麦草纤维素在4％盐酸、甲酸体系中的水解速率60、65、70和75°C时分别为0.0190h、0.0325h、0.0683h和0.0931h;但甲酸体系中葡萄糖也会发生一定的降解,在60、65、70和75°C时其速率分别为0.0285h、0.0448h、0.1098h和0.1436h。麦草纤维水解和葡萄糖降解的Arrhenius方程指前因子分别为:9.121014h和7.08×1015h。麦草纤维水解和葡萄糖降解的表观活化能分别为:106.35kJ/mol和111.00kJ/mol。因此,如何进一步抑制葡萄糖的水解,提高纤维素水解生成葡萄糖的效率仍值得进一步的研究。

摘要： 通过CP-MAS C-NMR和X-ray衍射分析了麦草纤维在甲酸体系中的水解过程,结果表明甲酸体系能有效的渗透到麦草纤维内部,使结晶区和非结晶区同时水解。同时也研究了麦草纤维甲酸体系中的水解动力学, 探讨了甲酸体系中盐酸浓度、固液比、反应温度、反应时间对麦草纤维水解的影响以及在该体系中葡萄糖的降解情况。分析了在该体系中葡萄糖的降解情况,结果表明葡萄糖的降解反应和纤维素的水解反应相比是个快反应。麦草纤维素在4％盐酸、甲酸体系中的水解速率60、65、70和75°C时分别为0.0190h、0.0325h、0.0683h和0.0931h;但甲酸体系中葡萄糖也会发生一定的降解,在60、65、70和75°C时其速率分别为0.0285h、0.0448h、0.1098h和0.1436h。麦草纤维水解和葡萄糖降解的Arrhenius方程指前因子分别为:9.121014h和7.08×1015h。麦草纤维水解和葡萄糖降解的表观活化能分别为:106.35kJ/mol和111.00kJ/mol。因此,如何进一步抑制葡萄糖的水解,提高纤维素水解生成葡萄糖的效率仍值得进一步的研究。

摘要： 本申请实施例提供一种纽扣电池、纽扣电池Xray检测设备和检测方法，Xray检测设备用于检测纽扣电池，Xray检测设备包括定位机构、移栽机构和Xray检测机构，定位机构包括CCD拍照模组和定位模组，CCD拍照模组设置在定位模组的上方，CCD拍照模组用于获取纽扣电池的二维码的位置，定位模组根据二维码的位置来调整纽扣电池的极耳的位置，使得Xray检测机构的X射线可以避开纽扣电池的极耳，移栽机构设置在定位模组的一侧，移栽机构用于将位置调整后的纽扣电池转移到Xray检测机构中，Xray检测机构用于检测电池的内部缺陷。本申请可以大大提高纽扣电池内部缺陷检测的准确性。

摘要： 本发明公开了一种XRAY专用输送线，包括主动轮、过渡轮、转向带轮、电机、输送带、光管，所述的光管设置在所述的XRAY专用输送线的下方，电机轴上装有作为主动轮的带轮，其余平行的带轮作为过渡轮，正交的带轮作为转向带轮，输送带盘绕在主动轮、过渡轮、转向带轮上，通过转向带轮实现正交盘绕。本发明采用一条皮带驱动输送线两侧，同步比常规的两侧各一条皮带更稳定，光管能够无限接近输送皮带底部，能尽可能的离被测物近，使光管检测到边缘也能满足离被测5mm的距离，保证了放大倍率。

摘要： 本实用新型公开了一种XRAY转码机专用传送线，包括传送组件，所述传送组件后端安装有移位组件，所述移位组件上安装有X光组件，所述传送组件内设有相机组件，所述传送组件包括两个侧架，两个所述侧架之间安装有若干线性阵列分布的导辊，侧架上安装有驱动导辊运行的导辊电机，位于传送组件后端的两根相邻导辊之间设有安装间隙，所述相机组件设于安装间隙内，所述相机组件包括两端固定在侧架上的固定梁，固定梁前端安装有相机导轨，本专用传送线可使不同尺寸的PCB超大板、软板、软硬结合板尽可能靠近相机组件，使相机本体能够正对板内层二维码进行拍照，满足不同尺寸和型材的PCB板内层二维码拍照成像清晰的需求。

摘要： 一种XRAY辐射剂量自动监控装置，它涉及放射性检测仪器技术领域。它包含底板、步进电机、小齿轮、大齿轮、旋转轴、壳体、玻璃面罩、XRAY辐射剂量检测器、监控、显示屏，所述底板上端设有步进电机，所述步进电机输出轴上设有小齿轮，所述小齿轮与大齿轮啮合，所述大齿轮设在旋转轴上，所述旋转轴下端与底板转动连接，旋转轴上端与壳体连接，所述壳体顶端设有玻璃面罩，所述玻璃面罩与壳体的空腔内设有XRAY辐射剂量检测器，所述XRAY辐射剂量检测器前端与监控相贯穿，所述XRAY辐射剂量检测器及监控与显示屏连接，所述壳体侧壁上开设有若干个通孔。它设计合理，XRAY辐射剂量监控装置能够360度无死角的进行XRAY辐射剂量的检测及监控，提高了XRAY辐射剂量监控的精准度。

摘要： 一种XRAY影像接收器倾斜45度机构，它涉及放射性检测仪器技术领域。它包含底座、第一立柱、第二立柱、旋转轴、第一支撑架、第二支撑架、放置平台、第一限位柱、第二限位柱，底座的上方设有第一立柱及第二立柱，第一立柱与第二立柱之间设有旋转轴，旋转轴上设有第一支撑架及第二支撑架，第一支撑架及第二支撑架顶部设有放置平台，底座上设有第一限位柱及第二限位柱，第一限位柱上端面呈45度角倾斜设置，第二限位柱上端面为水平面，第一限位柱及第二限位柱均设在第一支撑架或第二支撑架下方。它结构简单，设计合理，操作简单，能够快速有效的对XRAY影像接收器进行倾斜角度的调节，最大倾角为45度，从而提高了XRAY摄影的工作效率。

摘要： 本实用新型公开了一种XRAY专用输送线，包括主动轮、过渡轮、转向带轮、电机、输送带、光管，所述的光管设置在所述的XRAY专用输送线的下方，电机轴上装有作为主动轮的带轮，其余平行的带轮作为过渡轮，正交的带轮作为转向带轮，输送带盘绕在主动轮、过渡轮、转向带轮上，通过转向带轮实现正交盘绕。本实用新型采用一条皮带驱动输送线两侧，同步比常规的两侧各一条皮带更稳定，光管能够无限接近输送皮带底部，能尽可能的离被测物近，使光管检测到边缘也能满足离被测5mm的距离，保证了放大倍率。

摘要： 本实用新型公开了一种三段式XRAY设备缓冲区，包括上料等待区、检测区、出料等待区；所述的上料等待区、检测区、出料等待区沿物料输送方向顺次安装，所述的上料等待区两侧安装有第一开关门和第二开关门，所述的出料等待区的两侧安装有第三开关门和第四开关门；所述的第一开关门、第二开关门、第三开关门、第四开关门与光管连接。开关门的配合动作，使光管能够实现一直打开，不用关闭，大大节省了上料下料的时间。光管打开时间10s，光管安全关闭时间5s，机构缩短被测物输送时间3s，检测同一被测物，能够在上下料输送上节省18s。

摘要： 本实用新型公开了一种XRAY专用输送机，包括探测器运动机构、上料等待区、光管运动机构、检测区、出料等待区；上料等待区、检测区、出料等待区沿物料输送方向顺次安装，光管通过所述的光管运动机构安装在所述的检测区的下方，探测器通过所述的探测器运动机构安装在XRAY专用输送机的上部。被测物通过输送线进入设备上料等待区，被测物进入检测区，光管和探测器根据事先软件里编辑的工程，同步进行X/Y运动，采集图像数据，数据实时传输给主机进行图像处理，给出自动判断结果，同时被测物进入出料等待区，可对自动判断的不良品进行自动分拣，往复循环，实现设备的自动化运行，与产线的直接对接。

摘要： 本实用新型涉及一种XRay系统控制台，包括曝光设备，还包括主控平台、手持终端、曝光手闸；所述主控平台包括移动床控制逻辑模块、曝光控制逻辑电路、曝光开关和CAL控制模块，所述手持终端包括薄膜按键组、MCU和通讯电路，所述曝光手闸包括与主控平台中曝光控制逻辑电路输入端连接的曝光开关。本实用新型可以在隔离的操作间，解决射线防护问题，对XRay系统进行远程控制，减少X射线对人体的伤害。