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radiography Image Classification Using Deep Convolutional Neural Networks

Journal of Computer and Communications 2024年第6期12卷 199-209页

作者： Ahmad Chowdhury Haiyi Zhang Department of Computer Science Acadia University Wolfville Canada

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 n

关键词： CNN radiography Image Classification R Keras Chest X-Ray Machine Learning

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Contrast sensitivity in 14 MeV fast neutron radiography

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Nuclear Science and Techniques 2017年第6期28卷 115-122页

作者： Chang-Bing Lu Jie Bao Ying Huang Peng Xu Xiong-Jun Chen Qi-Wei Zhang Xi-Chao Ruan Key Laboratory of Nuclear Data China Institute of Atomic Energy Xi'an Institute of High Technology Science and Technology Information Center China Academy of Engineering Physics

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.

关键词： Fast neutron radiography Contrast sensitivity Experimental research

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Flash X-ray radiography technique to study the high velocity impact of soft projectile on E-glass/epoxy composite material

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Defence Technology（防务技术） 2019年第2期15卷 216-226页

作者： B.Venkata Ramudu C.Jayarami Reddy V.Madhu Armour Design and Development Division Defence Metallurgical Research Laboratory

In the present paper, the high velocity impact of 9 mm soft lead projectile on 10 mm and 30 mm thick Eglass/epoxy composites was studied using a 450 kV Flash X-ray radiography(FXR) system. The basic parameters of FXR imaging, such as effect of ratio of target to film(TF) and source to target(ST) distances and X-ray penetration thickness of the composite material were optimized based on clarity and the actual dimensions of the objects. The optimized parameters were used in the FXR imaging of the ballistic event of 9 mm soft projectile on E-glass/epoxy composite. The real time deformation patterns of both the projectile and composite target during the ballistic impact were captured and studied at different time intervals. The notable failure modes of the 10 mm thick target with time include fibre breakage, bulging on the back side, delamination, recovery of the bulging, reverse bulging and its recovery. However, with increase in thickness of the target to 30 mm the only failure mechanism observed is the breaking of fibres. The ballistic impact event was also numerically simulated using commercially available LS-DYNA software. The numerically simulated deformation patterns of the projectile and target at different time intervals are closely matching with the corresponding radiographic images.

关键词： Flash X-ray radiography E-Glass/epoxy composite Ballistic impact Numerical simulation

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Low Energy Plasma Focus as an Intense X-ray Source for radiography

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Plasma Science and Technology 2004年第3期6卷 2296-2300页

作者： S.Hussain M.Zakaullah Shujaat Ali A.Waheed Department of Physics Quaid-i-Azam University 45320 Islamabad PakistanDepartment of Physics Quaid-i-Azam University 45320 Islamabad PakistanDepartment of Physics Quaid-i-Azam University 45320 Islamabad PakistanPINSTECH P. O. Box 2151 44000 Islamabad Pakistan

Study on X-ray emission from a low energy (1.8 kJ) plasma focus devicepowered by a 9 μF capacitor bank, charged at 20 kV and giving peak discharge current of about 175kA by using a lead-inserted copper-tapered anode is reported. The X-ray yield in different energywindows is measured as a function of hydrogen filling pressure. The maximum yield in 4π-geometry isfound to be (27.3+-1.1) J and corresponding wall plug efficiency for X-ray generation is 1.52+-0.06%. X-ray emission, presumably due to bombarding activity of electrons in current sheath at theanode tip was dominant, which is confirmed by the pinhole images. The feasibility of the device asan intense X-ray source for radiography is demonstrated.

关键词： plasma focus X-ray source radiography

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Numerical study of point spread function of a fast neutron radiography system based on scintillating-fiber array

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Science China(Physics,Mechanics & Astronomy) 2007年第6期50卷 698-706页

作者： ZHANG FaQiang1,LI ZhengHong1,YANG JianLun1,YE Fan1,2,WANG Zhen1,2,XIA GuangXin1,YING ChunTong2 & LIU GuangJun2 1 Institute of Nuclear Physics and Chemistry,Mianyang 621900,China 2 Department of Engineering Physics,Tsinghua University,Beijing 100084,China Institute of Nuclear Physics and Chemistry Mianyang China Department of Engineering Physics Tsinghua University Beijing China

For a scintillating-fiber array fast-neutron radiography system,a point-spread-function computing model was introduced,and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources,the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200 μm×200 μm,the size of neutron source as small as a few millimeters,the distance between the source and the scintillating fiber array greater than 1 m,and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.

关键词： fast neutron radiography, scintillating-fiber array, point spread function, Monte Carlo simulation For a scintillating-fiber array fast-neutron radiography system, a point-spread- function computing model was introduced, and the simulation code was developed. The results of calculation show that fast-neutron radiographs vary with the size of fast neutron sources, the size of fiber cross-section and the imaging geometry. The results suggest that the following qualifications are helpful for a good point spread function: The cross-section of scintillating fibers not greater than 200μm×200μm, the size of neutron source as small as a few millimeters, the distance between the source and the scintillating fiber array greater than 1 m, and inspected samples placed as close as possible to the array. The results give suggestions not only to experiment considerations but also to the estimation of spatial resolution for a specific system.……

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Visualization and quantification of water movement in porous cement-based materials by real time thermal neutron radiography:Theoretical analysis and experimental study

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Science China(Technological Sciences) 2010年第5期53卷 1198-1207页

作者： ZHANG Peng1,WITTMANN F H1,2,ZHAO TieJun1,LEHMANN E3 & JIN ZuQuan1 1 Center for Durability & Sustainability Studies of Shandong Province,Qingdao Technological University,Qingdao 266033,China 2 Aedificat Institute Freiburg,Freiburg D-79100,Germany 3 Department of Spallation Neutron Source(ASQ),Paul Scherrer Institute,Villigen PSI CH-5232,Switzerland Center for Durability & Sustainability Studies of Shandong Province Qingdao Technological University Qingdao China Aedificat Institute Freiburg Freiburg Germany Department of Spallation Neutron Source (ASQ) Paul Scherrer Institute Villigen PSI Switzerland

Water movement in porous cement-based materials is of great importance when studying their deterioration processes and durability.Many traditional methods based on mass changes,electricity or nuclear magnetic resonances are available for studying water transport in cement-based materials.In this research,an advanced technique i.***.thermal neutron radiography was utilized to achieve visualization and quantification of time dependent water movement including water penetration and moisture vapor in porous cement-based materials through theoretical analysis and experimental study.Because thermal neutrons ex-perience a strong attenuation by hydrogen,neutron radiography exhibits high sensitivity to small amounts of water.A neutron transmission analysis for quantitative evaluation of raw radiographic measurements was developed and optimized based on point scattered functions(PScF).The determinations of the real time and space dependent water penetration into uncracked and cracked mortar samples,as well as the drying process have been presented in this paper.It is illustrated that thermal neutron radiography can be a useful research tool for visualization and quantification of water movement in porous building materials.The obtained results will help us to better understand deteriorating processes of cement-based materials and to find ways to improve their durability.

关键词： thermal neutron radiography visualization quantification water penetration moisture diffusion cement-based materials

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Simulation study on characteristics of information extraction in multiple-image radiography

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Nuclear Science and Techniques 2018年第5期29卷 87-97页

作者： Cui Zhang Xiao-Dong Pan Jing-Jie Ding Hong-Jie Shang Zhang-Gu Chen Yong-Fan Pu Gong-Ping Li School of Nuclear Science and Technology Lanzhou University Key Laboratory of Special Function Materials and Structure Design Ministry of Education Lanzhou University

Simulation experiments were performed to investigate the characteristics of information extraction in multiple-image radiography(MIR) based on geometrical optics approximation. Different Poisson noise levels were added to the simulation, and the results show that Poisson noise deteriorates the extraction results, with the degree of refraction > USAXS > absorption. The effects of Poisson noise are negligible when the detector's photon counts are about 1000 ph/pixel. A wider sampling range allows more accurate extraction results, but a narrower sampling range has a better signal-to-noise ratio for high Poisson noise levels, e.g., PN(10). The sampling interval can be suitably increased with a minor impact on the extraction results for low Poisson noise levels(PN(10000)). The extraction results are incomplete because a portion of the samplerocking curve is beyond the sampling range. This induces artifacts in the images, especially for strong refraction and USAXS signals. The artifacts are not obvious when the refraction angle and standard deviation of the USAXS are smaller than the sampling range by an order of magnitude.In general, the absorption barely affects the extraction results. However, additional Poisson noise will be generated when the sample is made of high-Z elements or has a large size due to the strong absorption. Here, the extraction results will deteriorate, and additional exposure time is required. This simulation provides important details on practical applications of MIR, with improvements in information extraction.

关键词： X-ray imaging Phase contrast Rocking curve Multiple-image radiography

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Evolution of the newest diagnostic methods for COVID-19:a Chinese perspective

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Journal of Zhejiang University-Science B(Biomedicine & Biotechnology) 2023年第6期24卷 463-484页

作者： Mingtao LIU Jiali LYU Xianhui ZHENG Zhiman LIANG Baoying LEI Huihuang CHEN Yiyin MAI Huimin HUANG Baoqing SUN Department of Clinical Laboratory National Center for Respiratory MedicineNational Clinical Research Center for Respiratory DiseaseState Key Laboratory of Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou510140China National Center for Respiratory Medicine National Clinical Research Center of Respiratory DiseaseState Key Laboratory of Respiratory DiseaseGuangzhou Institute of Respiratory Healththe First Affiliated Hospital of Guangzhou Medical UniversityGuangzhou 510140China Guangzhou Medical University Guangzhou 511495China

Coronavirus disease 2019(COVID-19)has continued to spread globally since late 2019,representing a formidable challenge to the world's healthcare systems,wreaking havoc,and spreading rapidly through human contact.With fever,fatigue,and a persistent dry cough being the hallmark symptoms,this disease threatened to destabilize the delicate balance of our global community.Rapid and accurate diagnosis of COVID-19 is a prerequisite for understanding the number of confirmed cases in the world or a region,and an important factor in epidemic assessment and the development of control measures.It also plays a crucial role in ensuring that patients receive the appropriate medical treatment,leading to optimal patient care.Reverse transcription-polymerase chain reaction(RT-PCR)technology is currently the most mature method for detecting viral nucleic acids,but it has many drawbacks.Meanwhile,a variety of COVID-19 detection methods,including molecular biological diagnostic,immunodiagnostic,imaging,and artificial intelligence methods have been developed and applied in clinical practice to meet diverse scenarios and needs.These methods can help clinicians diagnose and treat COVID-19 patients.This review describes the variety of such methods used in China,providing an important reference in the field of the clinical diagnosis of COVID-19.

关键词： Severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) Coronavirus disease 2019(COVID-19) Diagnosis Polymerase chain reaction(PCR) Immunoassay radiography

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Automatic detection of teeth and dental treatment patterns on dental panoramic radiographs using deep neural networks

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Forensic Sciences Research 2022年第3期7卷 456-466页

作者： Hye-Ran Choi Thomhert Suprapto Siadari Jo-Eun Kim Kyung-Hoe Huh Won-Jin Yi Sam-Sun Lee Min-Suk Heo Department of Oral and Maxillofacial Radiology and Dental Research Institute School of DentistrySeoul National UniversitySeoulRepublic of Korea Artificial Intelligence Research Centre Digital Dental Hub IncorporationSeoulRepublic of Korea Department of Oral and Maxillofacial Radiology Seoul National University Dental HospitalSeoulRepublic of Korea

Disaster victim identification issues are especially critical and urgent after a large-scale disaster.The aim of this study was to suggest an automatic detection of natural teeth and dental treatment patterns based on dental panoramic radiographs(DPRs)using deep learning to promote its applicability as human identifiers.A total of 1638 DPRs,of which the chronological age ranged from 20 to 49 years old,were collected from January 2000 to November 2020.This dataset consisted of natural teeth,prostheses,teeth with root canal treatment,and implants.The detection of natural teeth and dental treatment patterns including the identification of teeth number was done with a pre-trained object detection network which was a convolutional neural network modified by EfficientDet-D3.The objective metrics for the average precision were 99.1%for natural teeth,80.6%for prostheses,81.2%for treated root canals,and 96.8%for implants,respectively.The values for the average recall were 99.6%,84.3%,89.2%,and 98.1%,in the same order,respectively.This study showed outstanding performance of convolutional neural network using dental panoramic radiographs in automatically identifying teeth number and detecting natural teeth,prostheses,treated root canals,and implants.

关键词： Forensic sciences forensic odontology individual identification disaster victim identification radiography deep learning artificial intelligence

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In situ radiographic study of the grain refining behavior of Al_(3)Sc during the solidification of Al-10Cu alloy

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Journal of Materials Science & Technology 2022年第27期122卷 33-43页

作者： Yue Wu Yang Tang Ya Zhang Yanan Fu Hui Xing Jiao Zhang Jun Jiang Baode Sun Shanghai Key Lab of Advanced High-Temperature Materials and Precision Forming Shanghai Jiao Tong UniversityShanghai 200240PR China Shanghai Synchrotron Radiation Facility Shanghai Institute of Applied PhysicsCASShanghai 201204PR China State Key Lab of Metal Matrix Composites Shanghai Jiao Tong UniversityShanghai 200240PR China Collaborative Innovation Center for Advanced Ship and Deep-Sea Exploration Shanghai Jiao Tong UniversityShanghai 200240PR China Mechanical Engineering Department Imperial College LondonLondon SW72AZUK

Grain refinement of Al alloys inoculated by rare earth elements,such as Sc,has been extensively acknowledged,while the practical behavior of how inoculant Al_(3)Sc particles affect the refinement in solidification has not been clarified due to the non-transparency of the solidification process.Here,the microstructural evolution of primary Al_(3)Sc particles andα-Al grains in Al-10 wt.%Cu alloy solidifications with 0.2 wt.%,0.6 wt.%,and 1.0 wt.%Sc additions was investigated by in situ synchrotron X-ray radiography.The detailed mechanisms of curve motion of grains(CMG)and melt convection were revealed.The efficient grains nucleation,uniformly scattered small initial grains,and long duration of melt convection contributed to the best refinement in the 0.6 wt.%Sc addition sample.This work provides a deep insight into grain refinement in solidification with Sc addition,which will enlighten the composition design and casting process of Al alloys inoculated by rare earth elements.

关键词： radiography Solidification Melt convection Curve motion of grains Grain refining

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