2019 IEEE International Conference on Imaging Systems and Techniques (IST)最新文献_第5页

One-stage object detection networks for inspecting the surface defects of magnetic tiles 磁瓦表面缺陷检测的一级目标检测网络

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010098

Jiaqi Wei, Peiyuan Zhu, Xiang Qian, Shidong Zhu

{"title":"One-stage object detection networks for inspecting the surface defects of magnetic tiles","authors":"Jiaqi Wei, Peiyuan Zhu, Xiang Qian, Shidong Zhu","doi":"10.1109/IST48021.2019.9010098","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010098","url":null,"abstract":"One of the core components of the permanent magnet motor is magnetic tile and surface defect detection of it is of vital importance to ensure the performance and service life of the motor. This paper employs a deep learning method based on computer vision to detect the surface defects on magnetic tiles in order to replace manual inspection and increase productivity. Considering the real-time requirements of the industrial site, three designed one-stage object detection networks of different depth are compared on our Inner-R surface dataset of magnetic tiles. The whole image is input into the networks which regard the object detection as a regression problem and output the value of class probability and position coordinate of the object. This approach can detect more than one defects on the same image as well as the location of defects which provides advantages to find the number of defects per class and improve the manufacturing process. As the result shows, the YOLOv3 network is the most applicable one in this magnetic tile surface defect detection problem and the detection time is less than 23 ms, which is an eye-catching result.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117128100","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Design and Testing of a Square Helmholtz Coil for NMR Applications with Relative Improved B1 Homogeneity 具有相对改善B1均匀性的核磁共振方形亥姆霍兹线圈的设计和测试

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010469

S. A. Ghaly, K. AlMuhanna, M. O. Khan

{"title":"Design and Testing of a Square Helmholtz Coil for NMR Applications with Relative Improved B1 Homogeneity","authors":"S. A. Ghaly, K. AlMuhanna, M. O. Khan","doi":"10.1109/IST48021.2019.9010469","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010469","url":null,"abstract":"In this article, a radiofrequency (RF) coil that can produce a high electromagnetic field homogeneity to be used for Magnetic Resonance Imaging (MRI) applications is pondered. Helmholtz Coils are a special arrangement of loops such that when an electric current is applied to them, the resultant magnetic field generated between the coils is extremely uniform. Coils configured in this way are also used for applying or measuring fields and are useful for experiments and calibration where a known ambient magnetic field is required. Helmholtz coils play an important role to acquire magnetic resonance images with maintaining good magnetic field homogeneity. In this work, a square Helmholtz coil is designed and tested. The main objectives are to calculate the magnetic field provided by the square Helmholtz coils at any point in space and to show that it is uniform. Simulation is one of the most important parts of this work by which mathematical equations are simulated to investigate the axial magnetic field produced by square loops. Also, electrical modeling for Square Helmholtz coils is carried out. Besides this, the square Helmholtz coil is implemented experimentally and the theoretical and practical results are compared.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128364020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Local/Regional Based CAD System for Early Diagnosis of Alzheimer's Disease Using sMRI Scans 基于sMRI扫描的阿尔茨海默病早期诊断的局部/区域CAD系统

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010162

F. E. El-Gamal, M. Elmogy, A. Khalil, M. Ghazal, Hassan H. Soliman, A. Atwan, R. Keynton, G. Barnes, A. El-Baz

{"title":"A Local/Regional Based CAD System for Early Diagnosis of Alzheimer's Disease Using sMRI Scans","authors":"F. E. El-Gamal, M. Elmogy, A. Khalil, M. Ghazal, Hassan H. Soliman, A. Atwan, R. Keynton, G. Barnes, A. El-Baz","doi":"10.1109/IST48021.2019.9010162","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010162","url":null,"abstract":"Alzheimer's disease (AD) is one of the neurodegenerative diseases, an irreparable one, that targets the central nervous system and causes dementia. During its progression, the disease goes through a number of stages where the diagnosis of the disease at its early stage is highly recommended. Despite this recommendation, accomplishing this diagnosis task faces a number of obstacles including the variable impact of the disease on its sufferers. This paper mainly aims to assist in the early diagnosis process of AD through introducing a brain regional based computer-aided diagnosis (CAD) system, using structural magnetic resonance imaging (sMRI), that goes through four main stages: preprocessing, brain labeling, extracting the discriminant features, as well as diagnosing. The novelty of the our work is to offer a local/regional diagnosis to serve the subject-dependent effect of the disease followed by a global diagnosis with an overall promising performance as evaluated with the related work. The experimental results show accuracy of 96.6%, specificity of 100%, and sensitivity of 94.25%. Validating our system with the related work and some well-known classifiers shows promising results in addressing this research point.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124121921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving image reconstruction in electrical capacitance tomography based on deep learning 基于深度学习的电容层析成像图像重建改进

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010087

Hai Zhu, Jiangtao Sun, Lijun Xu, Shijie Sun

引用次数: 1

Imaging of flow pattern of gas-oil flows with convolutional neural network 基于卷积神经网络的油气流态成像

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010576

Zhuoqun Xu, Xinmeng Yang, Bing Chen, Maomao Zhang, Yi Li

{"title":"Imaging of flow pattern of gas-oil flows with convolutional neural network","authors":"Zhuoqun Xu, Xinmeng Yang, Bing Chen, Maomao Zhang, Yi Li","doi":"10.1109/IST48021.2019.9010576","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010576","url":null,"abstract":"Gas volume fraction (GVF) is an important parameter for the measurement of oil-gas two-phase flow. Online measurement of the GVF of oil and gas two-phase flow is of great significance for the safety monitoring and measurement of oilfield production processes. So it is an urgent problem to quickly and accurately detect the real-time GVF according to the non-destructive testing of oilfield field devices. In this paper, a method based on different flow rates and oil-gas ratios is proposed. The method of convolutional neural network (CNN) is used to predict the gas and oil flow rate in oil-gas two-phase flows. Compared with traditional algorithms, CNN algorithm solves the problem of the relationship between high-dimensional data (streaming image pixels) and low-dimensional data (GVF values and traffic) that cannot be solved by traditional algorithms. The data of different flow and oil-gas ratios of oil and gas two-phase flow were collected by experiment. The data collected by electrical capacitance tomography (ECT) was reconstructed using linear projection algorithm (LBP) to obtain the flow pattern. The reconstructed flow graphs are predicted by Binarized image measurement algorithm, SVM algorithm and convolutional neural network algorithm for oil flow rate, gas flow rate, and GVF. The average relative error of GVF prediction is 43% for Binarized image measurement algorithm, 8% for SVM algorithm, and 5% for the CNN algorithm. The CNN algorithm effectively avoids the possible over-fitting problem. Its loss function uses ElasticNet regression instead of least squares regression. The inception V3 model used is decomposed into small convolutions, which can reduce the amount of parameters, reduce over-fitting, and enhance the nonlinear expression of the network. The final model has an allowable error range of 5% and the accuracy can reach more than 90%.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128441537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

A CAD System for the Early Prediction of Hypertension based on Changes in Cerebral Vasculature 基于脑血管变化的高血压早期预测CAD系统

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010179

Heba Kandil, A. Soliman, F. Taher, M. Ghazal, Mohiuddin Hadi, G. Giridharan, A. El-Baz

{"title":"A CAD System for the Early Prediction of Hypertension based on Changes in Cerebral Vasculature","authors":"Heba Kandil, A. Soliman, F. Taher, M. Ghazal, Mohiuddin Hadi, G. Giridharan, A. El-Baz","doi":"10.1109/IST48021.2019.9010179","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010179","url":null,"abstract":"Hypertension is a leading cause for mortality in the US and a significant contributor to many vascular and non vascular diseases. Previous literature reports suggest that specific cerebral vascular alterations precede the onset of hypertension. In this manuscript, we propose a magnetic resonance angiography (MRA)-based computer-aided-diagnosis (CAD) system for the early detection of hypertension. The steps of the proposed CAD system are: 1) preprocessing of the MRA input data to correct the bias resulting from the magnetic field, remove noise effects, reduce contrast non-uniformities, enhance homogeneity using a generalized Gauss-Markov random field (GGMRF), and normalize data to enhance the segmentation process, 2) delineating the cerebral vasculature using a deep 3-D convolutional neural network (CNN) automatically and accurately, 3) extraction of vascular features (cerebrovascular diameters and tortuosity) that are reported to change with the progression of hypertension and constructing the feature vectors, 4) using the feature vectors for classifying input data using a support vector machine (SVM) classifier. We report a 90% classification accuracy in distinguishing between normal and potential hypertensive subjects. These results demonstrate the efficacy of using the proposed vascular features to predict pre-hypertension or hypertension. Clinicians could track the alterations of these vascular features over time for people at risk of developing hypertension for optimal medical management and mitigate adverse events.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"75 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130978892","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Identifying and Characterizing the 18 Steps of Medical Imaging Process Workflow as a Basis for Targeting Improvements in Clinical Practice 识别和描述医学成像过程工作流程的18个步骤，作为临床实践中针对性改进的基础

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010117

M. S. Jabin, C. Mandel, T. Schultz, P. Hibbert, F. Magrabi, W. Runciman

{"title":"Identifying and Characterizing the 18 Steps of Medical Imaging Process Workflow as a Basis for Targeting Improvements in Clinical Practice","authors":"M. S. Jabin, C. Mandel, T. Schultz, P. Hibbert, F. Magrabi, W. Runciman","doi":"10.1109/IST48021.2019.9010117","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010117","url":null,"abstract":"We reviewed initiatives to improve the quality and safety of health information technology in medical imaging through the lens of incident reports provided by healthcare professionals in each sequential step of the medical imaging process workflow. The 18 steps of imaging workflow were framed based on a literature review, visits to hospital radiology departments, interviews with radiologists, and iterative consultations with experts. Both inductive and deductive analyses were applied to 436 health information technology-related incidents identified from 4,915 medical imaging incident reports. In the 18 imaging workflow steps both human (58%) and technical factors (42%) were involved. Classification from the perspective of the 18 steps of the imaging workflow was useful because it orientates the reporter and analysts to the tasks at each stage, and it also informs the analysts as to where corrective strategies could be addressed. Most of the things that go wrong in healthcare occur infrequently, so collecting information after they have gone wrong is the only practical approach to identifying and characterizing them. This should become a routine part of clinical practice in a complex constantly changing system.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123767802","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

Super-Resolution Spike Event-based Polarimetric Dynamic Vision Sensor p(DVS) Cognitive Imaging 超分辨率脉冲事件极化动态视觉传感器认知成像

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010257

Anthony Beninati, Martin Nowak, Nicolas Douard, Joe Lanzi, Ridwan Hussain, Yi Wang, S. Shrestha, Zoe Giakos, G. Giakos

引用次数: 0

A Multi-frequency WMS Method for Tunable Diode Laser Absorption Spectroscopy Tomography 可调谐二极管激光吸收光谱层析成像的多频WMS方法

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/ist48021.2019.9010545

Ang Huang, Z. Cao, Wenshuai Zhao, Lijun Xu

{"title":"A Multi-frequency WMS Method for Tunable Diode Laser Absorption Spectroscopy Tomography","authors":"Ang Huang, Z. Cao, Wenshuai Zhao, Lijun Xu","doi":"10.1109/ist48021.2019.9010545","DOIUrl":"https://doi.org/10.1109/ist48021.2019.9010545","url":null,"abstract":"In this paper, a multi-frequency wavelength modulation spectroscopy (WMS) method for tunable diode laser absorption spectroscopy (TDLAS) tomography was proposed. Multiple wavelengths modulated at different frequencies were used to extract the absorption spectrums in parallel along various laser paths. For a five-view fan-beam TDLAS sensor, the wavelength of incident laser was respectively modulated by the high-frequency sinusoidal signal at six different frequencies to separate absorption spectrums at different angles and different wavelengths and then distributions of temperature and water vapor's molecules concentration can be reconstructed. The framerate of the proposed multi-frequency WMS method for image reconstruction is ten times faster than single-frequency WMS method with cascade laser scanning. Numerical simulations were conducted to verify the effectiveness of the proposed method with two absorption spectra of water molecule, $nu$ 1=7185 cm−1 and $nu$ 2=7444 cm−1. Three different distributions of temperature and water vapor's molecules concentration were fabricated and reconstructed.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128238617","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Autism Spectrum Disorder Diagnosis framework using Diffusion Tensor Imaging 使用扩散张量成像的自闭症谱系障碍诊断框架

2019 IEEE International Conference on Imaging Systems and Techniques (IST) Pub Date : 2019-12-01 DOI: 10.1109/IST48021.2019.9010186

Y. Elnakieb, G. Barnes, A. El-Baz, A. Soliman, Ali M. Mahmoud, Omar Dekhil, A. Shalaby, M. Ghazal, A. Khalil, A. Switala, R. Keynton

{"title":"Autism Spectrum Disorder Diagnosis framework using Diffusion Tensor Imaging","authors":"Y. Elnakieb, G. Barnes, A. El-Baz, A. Soliman, Ali M. Mahmoud, Omar Dekhil, A. Shalaby, M. Ghazal, A. Khalil, A. Switala, R. Keynton","doi":"10.1109/IST48021.2019.9010186","DOIUrl":"https://doi.org/10.1109/IST48021.2019.9010186","url":null,"abstract":"Autism is a complex neurological disorder which affects behavioral and communication skills. Numerous studies were presented suggesting abnormal development of neural networks in the brain in shape, functionality, and/or connectivity. While conventional diagnosis of autism is subjective and requires long time before confirmation, neuro-imaging techniques provide a promising alternative. This paper introduces an automated autism computer-aided diagnosis system based on the connectivity information of the WM tracts. In this CAD system, two consecutive levels of analysis are implemented: Local analysis utilizing diffusion tensor imaging (DTI) data, then getting global decision. Johns Hopkins WM areas' atlas is employed for DTI-volumes segmentation. Correlations of DTI-derived features between different areas in the brain, demonstrating linkage between WM areas were exploited. Then, feature selection extracting the most prominent features among those associations are made. Lastly, an SVM classifier is exploited to produce the final diagnostic decision. We tested our proposed system on a large data set of 263 subjects from NDAR database (141 typically developed subjects: 66 males, and 75 females, and 122 autistics: 66 males, and 56 females), with ages ranging from 96 to 215 months, achieving an overall accuracy of 71%, with Leave-one-subject-out validation.","PeriodicalId":117219,"journal":{"name":"2019 IEEE International Conference on Imaging Systems and Techniques (IST)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129280587","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4