In recent times, the COVID-19 epidemic turn out to be increased in an extreme manner, by the accessibility of an inadequate amount of rapid testing kits. Consequently, it is essential to develop the automated techniques for Covid-19 detection to recognize the existence of disease from the radiological images. The most ordinary symptoms of COVID-19 are sore throat, fever, and dry cough. Symptoms are able to progress to a rigorous type of pneumonia with serious impediment. As medical imaging is not recommended currently in Canada for crucial COVID-19 diagnosis, systems of computer-aided diagnosis might aid in early COVID-19 abnormalities detection and help out to observe the disease progression, reduce mortality rates potentially. In this approach, a deep learning based design for feature extraction and classification is employed for automatic COVID-19 diagnosis from computed tomography (CT) images. The proposed model operates on three main processes based pre-processing, feature extraction, and classification. The proposed design incorporates the fusion of deep features using GoogLe Net models. Finally, Multi-scale Recurrent Neural network (RNN) based classifier is applied for identifying and classifying the test CT images into distinct class labels. The experimental validation of the proposed model takes place using open-source COVID-CT dataset, which comprises a total of 760 CT images. The experimental outcome defined the superior performance with the maximum sensitivity, specificity, and accuracy.
{"title":"Automatic Segmentation and Classification of COVID-19 CT Image Using Deep Learning and Multi-Scale Recurrent Neural Network Based Classifier","authors":"R. Subhalakshmi, S. Balamurugan, S. Sasikala","doi":"10.1166/jmihi.2021.3850","DOIUrl":"https://doi.org/10.1166/jmihi.2021.3850","url":null,"abstract":"In recent times, the COVID-19 epidemic turn out to be increased in an extreme manner, by the accessibility of an inadequate amount of rapid testing kits. Consequently, it is essential to develop the automated techniques for Covid-19 detection to recognize the existence of disease from the radiological images. The most ordinary symptoms of COVID-19 are sore throat, fever, and dry cough. Symptoms are able to progress to a rigorous type of pneumonia with serious impediment. As medical imaging is not recommended currently in Canada for crucial COVID-19 diagnosis, systems of computer-aided diagnosis might aid in early COVID-19 abnormalities detection and help out to observe the disease progression, reduce mortality rates potentially. In this approach, a deep learning based design for feature extraction and classification is employed for automatic COVID-19 diagnosis from computed tomography (CT) images. The proposed model operates on three main processes based pre-processing, feature extraction, and classification. The proposed design incorporates the fusion of deep features using GoogLe Net models. Finally, Multi-scale Recurrent Neural network (RNN) based classifier is applied for identifying and classifying the test CT images into distinct class labels. The experimental validation of the proposed model takes place using open-source COVID-CT dataset, which comprises a total of 760 CT images. The experimental outcome defined the superior performance with the maximum sensitivity, specificity, and accuracy.","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"80 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126203165","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}
{"title":"Classification of Tumor of MRI Brain Image Using Hybrid Feature Extraction Method and Support Vector Machine Classifier","authors":"K. Kavinkumar, T. Meeradevi","doi":"10.1166/JMIHI.2021.3842","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3842","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131173116","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}
{"title":"Analysis on Ensemble Methods for the Prediction of Cardiovascular Disease","authors":"C. Murale, M. Sundarambal, R. Nedunchezhian","doi":"10.1166/JMIHI.2021.3839","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3839","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123370608","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}
Mie Ishii, Mai Nakamura, R. Ishii, K. Shida, T. Hatada, N. Murakami, Megumi Maeda, Rumi Okamoto, Sae Shinohara, F. Araki, Y. Higashida
{"title":"Effect of Compression Force and Target or Target/Filter Combination on Mean Glandular Dose for Japanese Women in Full-Field Digital Mammography System","authors":"Mie Ishii, Mai Nakamura, R. Ishii, K. Shida, T. Hatada, N. Murakami, Megumi Maeda, Rumi Okamoto, Sae Shinohara, F. Araki, Y. Higashida","doi":"10.1166/JMIHI.2021.3862","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3862","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131525602","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}
{"title":"Semantic Content-Based Image Retrieval System Using Deep Learning Model for Lung Cancer CT Images","authors":"T. Rajasenbagam, S. Jeyanthi","doi":"10.1166/JMIHI.2021.3859","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3859","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133597878","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}
J. Shanthini, P. Arunkumar, S. Karthik, N. Karthikeyan
{"title":"Interpretation of Gait Supervising Mechanism Using Sensor Integrated Makeshift and Analysing Pattern by K-Means Clustering Algorithm","authors":"J. Shanthini, P. Arunkumar, S. Karthik, N. Karthikeyan","doi":"10.1166/JMIHI.2021.3847","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3847","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122374769","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}
{"title":"Design of System Level Architecture of Multi-Core with Array Mapping Based on Floating Processing Factor-Fast Fourier Transform for Health Informatics Application","authors":"T. Sivaprakasam, M. Ramasamy","doi":"10.1166/JMIHI.2021.3852","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3852","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127091738","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}
{"title":"Modeling of TST Using Biological Signals and KL-Hausdorff Distance Similarity Measure for Gene Based Parkinson's Disease Recognition","authors":"B. Anusha, P. Geetha","doi":"10.1166/JMIHI.2021.3843","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3843","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114512803","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}
{"title":"A Novel Tuberculosis Prediction Model by Extracting Radiological Features Present in Chest X-ray Images Using Modified Discrete Grey Wolf Optimizer Based Segmentation","authors":"J. Kumar, S. Balamurugan, S. Sasikala","doi":"10.1166/JMIHI.2021.3837","DOIUrl":"https://doi.org/10.1166/JMIHI.2021.3837","url":null,"abstract":"","PeriodicalId":393031,"journal":{"name":"J. Medical Imaging Health Informatics","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126281508","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}
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