Int. J. E Health Medical Commun.最新文献

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Advanced Object Detection in Bio-Medical X-Ray Images for Anomaly Detection and Recognition 生物医学x射线图像中用于异常检测和识别的高级目标检测
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/ijehmc.2021030106
Garv Modwel, Anu Mehra, N. Rakesh, K. Mishra
{"title":"Advanced Object Detection in Bio-Medical X-Ray Images for Anomaly Detection and Recognition","authors":"Garv Modwel, Anu Mehra, N. Rakesh, K. Mishra","doi":"10.4018/ijehmc.2021030106","DOIUrl":"https://doi.org/10.4018/ijehmc.2021030106","url":null,"abstract":"The human vision system is mimicked in the format of videos and images in the area of computer vision. As humans can process their memories, likewise video and images can be processed and perceptive with the help of computer vision technology. There is a broad range of fields that have great speculation and concepts building in the area of application of computer vision, which includes automobile, biomedical, space research, etc. The case study in this manuscript enlightens one about the innovation and future scope possibilities that can start a new era in the biomedical image-processing sector. A pre-surgical investigation can be perused with the help of the proposed technology that will enable the doctors to analyses the situations with deeper insight. There are different types of biomedical imaging such as magnetic resonance imaging (MRI), computerized tomographic (CT) scan, x-ray imaging. The focused arena of the proposed research is x-ray imaging in this subset. As it is always error-prone to do an eyeball check for a human when it comes to the detailing. The same applied to doctors. Subsequently, they need different equipment for related technologies. The methodology proposed in this manuscript analyses the details that may be missed by an expert doctor. The input to the algorithm is the image in the format of x-ray imaging; eventually, the output of the process is a label on the corresponding objects in the test image. The tool used in the process also mimics the human brain neuron system. The proposed method uses a convolutional neural network to decide on the labels on the objects for which it interprets the image. After some pre-processing the x-ray images, the neural network receives the input to achieve an efficient performance. The result analysis is done that gives a considerable performance in terms of confusion factor that is represented in terms of percentage. At the end of the narration of the manuscript, future possibilities are being traces out to the limelight to conduct further research.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"672 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122971900","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
Application-Specific Discriminant Analysis of Cardiac Anomalies Using Shift-Invariant Wavelet Transform 基于平移不变小波变换的心脏异常判别分析
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/IJEHMC.20210701.OA5
Ritu Singh, N. Rajpal, R. Mehta
{"title":"Application-Specific Discriminant Analysis of Cardiac Anomalies Using Shift-Invariant Wavelet Transform","authors":"Ritu Singh, N. Rajpal, R. Mehta","doi":"10.4018/IJEHMC.20210701.OA5","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210701.OA5","url":null,"abstract":"Automatic arrhythmia detection in electrocardiogram (ECG) using supervised learning has gained significant considerations in recent years. This paper projects the performance analysis of classifiers such as support vector machine (SVM), extreme learning machine (ELM), and k-nearest neighbor (KNN) with efficient time utilization showing multi-classification for specific medical application. The wavelet double decomposition is used to show the shift-invariant use of dual-tree complex wavelet transform for noise filtering and beat segmentation is done to extract 130 informative samples. Further, the linear discriminant analysis is applied to dimensionally reduce and elite the 12 most relevant features for classifying normal and four abnormal beats collected from MIT/BIH ECG database. The proposed executed system distinguishes SVM, ELM, and KNN with percentage accuracy of 99.8, 97, and 99.8 having classifier testing time as 0.0081s, 0.0031s, and 0.0234s, respectively. The simulated experimental outcomes in comparison with existing work yields adequate accuracy, and computational time.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114189579","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: 2
Robust and Secure Watermarking for Propagation of Digital Multimedia by Paillier Homomorphic Cryptosystem With Arnold Transformation 基于Arnold变换的Paillier同态密码系统在数字多媒体传播中的鲁棒安全水印
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/IJEHMC.20210701.OA2
Namita Agarwal, P. Singh
{"title":"Robust and Secure Watermarking for Propagation of Digital Multimedia by Paillier Homomorphic Cryptosystem With Arnold Transformation","authors":"Namita Agarwal, P. Singh","doi":"10.4018/IJEHMC.20210701.OA2","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210701.OA2","url":null,"abstract":"Sharing of digital media over internet is becoming easier due to content authentication and security provided by digital watermarking. It also locates application in other fields like copyright protection, tele-medicine, military, tamper detection, and many more. This paper represents the robust watermarking approach using Paillier homomorphic cryptosystem with Arnold transformation. In this, the watermarking system is primarily prepared at an encrypted DWT-DCT domain. Cryptosystem is exploited at this time to encrypt the original media. For more security of multimedia content, the watermark image is scrambled through Arnold scrambling technique. The embedding process is done here to produce the encrypted watermark image followed by the encryption process. At recovery phase, decryption of encrypted watermark image to get the original and watermark image is done. The experimental result has shown that watermarking method is more robust and offers the security of digital media.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115873315","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: 2
Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps 声带分析对声音障碍的检测和分类:声带息肉的检测和分类
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/IJEHMC.20210701.OA6
Vikas Mittal, R. Sharma
{"title":"Vocal Folds Analysis for Detection and Classification of Voice Disorder: Detection and Classification of Vocal Fold Polyps","authors":"Vikas Mittal, R. Sharma","doi":"10.4018/IJEHMC.20210701.OA6","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210701.OA6","url":null,"abstract":"The detection and description of pathological voice are the most important applications of voice profiling. Currently, techniques like laryngostroboscopy or surgical microlarynoscopy are popularly used for the diagnosis of voice pathologies but are invasive in nature. Disorders of vocal folds impact the quality of voice, and therefore, the accuracy of voice profiling is reduced. This paper presents a better solution to differentiate normal and pathological voices based on the glottal, physical, and acoustic and equivalent electrical parameters. These parameters have been correlated using mathematical equations and models. Results reveal that the glottal flow is strongly influenced by physical parameters like stiffness and viscosity of vocal folds in case of pathological voice. However, their direct measurement requires complex invasive medical procedures or costly and complex electronic hardware arrangements in case of non-invasive methods. Glottal parameters, on the other hand, facilitate much simpler estimation of vocal folds disorders. In this work, the authors have presented two non-invasive approaches for better accuracy and least complexity for differentiating normal and pathological voices: 1) by using correlation of glottal and physical parameters, 2)by using acoustic and equivalent electrical parameters.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114186042","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
Prediction of Environmental Pollution Using Hybrid PSO-K-Means Approach 混合pso - k -均值法预测环境污染
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/ijehmc.2021030104
M. Mahajan, Santosh Kumar, B. Pant
{"title":"Prediction of Environmental Pollution Using Hybrid PSO-K-Means Approach","authors":"M. Mahajan, Santosh Kumar, B. Pant","doi":"10.4018/ijehmc.2021030104","DOIUrl":"https://doi.org/10.4018/ijehmc.2021030104","url":null,"abstract":"Air pollution is increasing day by day, decreasing the world economy, degrading the quality of life, and resulting in a major productivity loss. At present, this is one of the most critical problems. It has a significant impact on human health and ecosystem. Reliable air quality prediction can reduce the impact it has on the nearby population and ecosystem; hence, improving air quality prediction is the prime objective for the society. The air quality data collected from sensors usually contains deviant values called outliers which have a significant detrimental effect on the quality of prediction and need to be detected and eliminated prior to decision making. The effectiveness of the outlier detection method and the clustering methods in turn depends on the effective and efficient choice of parameters like initial centroids and number of clusters, etc. The authors have explored the hybrid approach combining k-means clustering optimized with particle swarm optimization (PSO) to optimize the cluster formation, thereby improving the efficiency of the prediction of the environmental pollution.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123152616","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: 2
An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images 基于人工智能的早期青光眼OCT图像识别系统
Int. J. E Health Medical Commun. Pub Date : 2021-07-01 DOI: 10.4018/IJEHMC.20210701.OA3
Law Kumar Singh, Pooja, H. Garg, Munish Khanna
{"title":"An Artificial Intelligence-Based Smart System for Early Glaucoma Recognition Using OCT Images","authors":"Law Kumar Singh, Pooja, H. Garg, Munish Khanna","doi":"10.4018/IJEHMC.20210701.OA3","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210701.OA3","url":null,"abstract":"Glaucoma is a progressive and constant eye disease that leads to a deficiency of peripheral vision and, at last, leads to irrevocable loss of vision. Detection and identification of glaucoma are essential for earlier treatment and to reduce vision loss. This motivates us to present a study on intelligent diagnosis system based on machine learning algorithm(s) for glaucoma identification using three-dimensional optical coherence tomography (OCT) data. This experimental work is attempted on 70 glaucomatous and 70 healthy eyes from combination of public (Mendeley) dataset and private dataset. Forty-five vital features were extracted using two approaches from the OCT images. K-nearest neighbor (KNN), linear discriminant analysis (LDA), decision tree, random forest, support vector machine (SVM) were applied for the categorization of OCT images among the glaucomatous and non-glaucomatous class. The largest AUC is achieved by KNN (0.97). The accuracy is obtained on fivefold cross-validation techniques. This study will facilitate to reach high standards in glaucoma diagnosis.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"217 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114415800","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: 8
The Healing Hearts at Home© Mobile Application Usability and Influence on Parental Perceived Stress: A Pilot Study 家庭疗愈之心©移动应用可用性及其对父母感知压力的影响:一项试点研究
Int. J. E Health Medical Commun. Pub Date : 2021-05-01 DOI: 10.4018/IJEHMC.20210501.OA6
V. Miller, Jennifer Newcombe, P. Radovich, F. Johnston, E. Medina, Anna Nelson
{"title":"The Healing Hearts at Home© Mobile Application Usability and Influence on Parental Perceived Stress: A Pilot Study","authors":"V. Miller, Jennifer Newcombe, P. Radovich, F. Johnston, E. Medina, Anna Nelson","doi":"10.4018/IJEHMC.20210501.OA6","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210501.OA6","url":null,"abstract":"In this study, the Healing Hearts and Home© (HHH©) application was piloted to determine the usability and usefulness of the mobile application and whether the application had an effect on caregivers' coping and stress. A posttest consisting of the Systems Usability Scale (SUS), the Coping Health Inventory for Parents (CHIP), and the Perceived Stress Scale (PSS) was used to collect information on the application usability, coping patterns, and perceived stress. Key informants provided more insight into usefulness. The SUS rating was 86.94 (SD = 6.34). The excellent usability score did not translate into uptake, though interest remained. The PSS scores for the control group 17.11 (SD = 1.69) and the intervention group were 19.11 (SD = 6.51) were not statistically different. None of the CHIP subscales predicted the PSS score. The HHH© application shows potential to reduce stress and improve coping in caregivers in the absence of available in-person intervention.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"7 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120900505","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: 2
Study of Healthcare Annotation Systems 医疗保健注释系统的研究
Int. J. E Health Medical Commun. Pub Date : 2021-05-01 DOI: 10.4018/IJEHMC.20210501.OA5
Khalil Chehab, Anis Kalboussi, A. Kacem
{"title":"Study of Healthcare Annotation Systems","authors":"Khalil Chehab, Anis Kalboussi, A. Kacem","doi":"10.4018/IJEHMC.20210501.OA5","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210501.OA5","url":null,"abstract":"The annotation practice is an almost daily activity used by healthcare professionals (PHC) to analyze patients' records, collaborate, share knowledge, and communicate. These annotations are generated within a healthcare cycle. Similarly, this cycle represents the life cycle of annotations in the patient record. The exponential increase in the number of medical annotation systems made the choice of a system by a PHC difficult, in a well-defined context (biology, radiology) and according to his/her needs to the functionalities offered by these tools. Therefore, the authors propose two taxonomies to distinguish annotation tools developed by industry and academia over the last two decades. The first classification provides an external vision based on five generic criteria. The second classification is an internal vision that gives us an idea about the functionalities offered by these systems. Finally, these unified and integrated classifications criteria are used to organize and observe the limitation of 50 medical annotation tool systems.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884752","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
Photoplethysmography Heart Rate Monitoring: State-of-the-Art Design 光电容积脉搏图心率监测:最先进的设计
Int. J. E Health Medical Commun. Pub Date : 2021-05-01 DOI: 10.4018/IJEHMC.20210501.OA2
E. A. Feukeu, S. Winberg
{"title":"Photoplethysmography Heart Rate Monitoring: State-of-the-Art Design","authors":"E. A. Feukeu, S. Winberg","doi":"10.4018/IJEHMC.20210501.OA2","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210501.OA2","url":null,"abstract":"Research conducted by the World Health Organisation (WHO) in 2018 demonstrated that the worldwide threat of cardiovascular diseases (CVDs) has increased compared to previous years. CVDs are very dangerous: if timely treatment is not performed, these conditions could become irreversible and lead to sudden death. Prescriptive measures include physical exercises and monitoring of the heart rate (HR). Despite the existence of various HR monitoring devices (or HMDs), a major challenge remains their availability, particularly to people in lower-income countries. Unfortunately, it is also this segment of the population that is the most vulnerable to CVDs. Accordingly, this led the authors to propose the design for an easily constructible state-of-the-art HMD that attempts to provide a highly accessible, lower-cost, and long-lasting solution that would be more affordable and accessible to these low-income communities.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115857558","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
Towards Better Segmentation of Abnormal Part in Multimodal Images Using Kernel Possibilistic C Means Particle Swarm Optimization With Morphological Reconstruction Filters: Combination of KFCM and PSO With Morphological Filters 形态学重构滤波器核可能性C均值粒子群优化在多模态图像异常部分分割中的应用:KFCM和粒子群算法与形态学滤波器的结合
Int. J. E Health Medical Commun. Pub Date : 2021-05-01 DOI: 10.4018/IJEHMC.20210501.OA4
R. Sumathi, Venkatesulu Mandadi
{"title":"Towards Better Segmentation of Abnormal Part in Multimodal Images Using Kernel Possibilistic C Means Particle Swarm Optimization With Morphological Reconstruction Filters: Combination of KFCM and PSO With Morphological Filters","authors":"R. Sumathi, Venkatesulu Mandadi","doi":"10.4018/IJEHMC.20210501.OA4","DOIUrl":"https://doi.org/10.4018/IJEHMC.20210501.OA4","url":null,"abstract":"The authors designed an automated framework to segment tumors with various image sequences like T1, T2, and post-processed MRI multimodal images. Contrast-limited adaptive histogram equalization method is used for preprocessing images to enhance the intensity level and view the tumor part clearly. With the combination of kernel possibilistic c means clustering with particle swarm optimization technique, a tumor part is segmented, and morphological filters are applied to remove the unrelated outlier pixels in the segmented image to detect the accurate tumor part. The authors collected various image sequences from online resources like Harvard brain dataset, BRATS, and RIDER, and a few from clinical datasets. Efficiency is ensured by computing various performance metrics like Jaccard Index MSE, PSNR, sensitivity, specificity, accuracy, and computational time. The proposed approach yields 97.06% segmentation accuracy and 98.08% classification accuracy for multimodal images with an average of 5s for all multimodal images.","PeriodicalId":375617,"journal":{"name":"Int. J. E Health Medical Commun.","volume":"129 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127088856","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: 3
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