Submit your paper : editorIJETjournal@gmail.com Paper Title : DESIGN AND DEVELOPE DEEP MODELS TO INVESTIGATE COVID-19 USING DEEP LEARNING LUS IMAGES ISSN : 2395-1303 Year of Publication : 2021 10.29126/23951303/IJET-V7I5P4 MLA Style: -Dr. D.J. Samatha Naidu, P.Panchajanya Kumar Reddy , DESIGN AND DEVELOPE DEEP MODELS TO INVESTIGATE COVID-19 USING DEEP LEARNING LUS IMAGES " " Volume 7 - Issue 5 September - October,2021 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org APA Style: -Dr. D.J. Samatha Naidu, P.Panchajanya Kumar Reddy " DESIGN AND DEVELOPE DEEP MODELS TO INVESTIGATE COVID-19 USING DEEP LEARNING LUS IMAGES " Volume 7 - Issue 5 September - October,2021 International Journal of Engineering and Techniques (IJET) ,ISSN:2395-1303 , www.ijetjournal.org Abstract - In medical imaging deep learning has successfully proved in the wake of the recent COVID19 pandemic situation, some works have started to investigate DL based solutions for the assisted diagnosis of lung diseases. In this project previous works focus on CT scans reports, this paper studies the application of DL techniques for the analysis of lung ultrasonography (LUS) images. we present a dataset of LUS images collected from several Italian hospitals, with labels indicating the degree of disease severity at a frame-level, video level, and pixel-level.by checking these data, introduce many deep models that address relevant tasks to analyse the LUS images automatically Reference [1] WHO, “Laboratory testing strategy recommendations for COVID19: Interim guidance,” Tech.Rep,2020.[Online].Available:https://apps.who.int/iris/bit stream/handle/10665/331509/WHOCOVID-19-lab testing2020.1-eng.pdf [2] R. Niehus, P. M. D. Salazar, A. Taylor, and M. Lipsitch, “Quantifying bias of COVID-19 prevalence and severity estimates in Wuhan, China that depend on reported cases in international travelers,” medRxiv, p. 2020.02.13.20022707, feb 2020. [3] Y. Yang et al., “Evaluating the accuracy of different respiratory specimens in the laboratory diagnosis and monitoring the viral shedding of 2019-nCoV infections,” medRxiv, p. 2020.02.11.20021493, feb 2020. [4] S. Salehi, A. Abedi, S. Balakrishnan, and A. Gholamrezanezhad, “Coronavirus Disease 2019 (COVID-19): A Systematic Review of Imaging Findings in 919 Patients,” Am J Roentgenol, pp. 1–7, mar 2020. [5] A. Bernheim et al., “Chest CT Findings in Coronavirus Disease-19 (COVID-19): Relationship to Duration of Infection,” Radiology, p. 200463, feb 2020. [Online]. Available: http://pubs.rsna.org/doi/10.1148/radiol.2020200463 [6] F. Mojoli, B. Bouhemad, S. Mongodi, and D. Lichtenstein, “Lung ultrasound for critically ill patients,” pp. 701–714, mar 2019. [7] R. Raheja, M. Brahmavar, D. Joshi, and D. Raman, “Application of Lung Ultrasound in Critical Care Setting: A Review,” Cureus, vol. 11, no. 7, jul 2019. [8] Y. Amatya, J. Rupp, F. M. Russell, J. Saunders, B. Bales, and D. R. House, “Diagnostic use of lung ultrasound compared to chest radiograph for suspected pneumonia in a resource-limited setting,” International Journal of Emergency Medicine, vol. 11, no. 1, dec 2018. [9] E. Poggiali et al., “Can Lung US Help Critical Care Clinicians in the Early Diagnosis of Novel Coronavirus (COVID-19) Pneumonia?” Radiology, p. 200847, mar 2020. [10] Q. Y. Peng et al., “Findings of lung ultrasonography of novel corona virus pneumonia during the 2019 – 2020 epidemic,” Intensive Care Medicine, no. 87, pp. 6–7, mar 2020 Keywords — |