A Deep Learning Neural Network Techniques in Visualization, Imaging Data Acquisition And Diagnosis for Covid-19

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Dr. N. Danapaquiame, et. al.

Abstract

The corona virus disease pandemic of 2019 (COVID-19) is sweeping the globe. Medical imaging, such as X-ray and computed tomography (CT), is critical in the global fight against COVID-19, and recently evolving artificial intelligence (AI) technologies are enhancing the capacity of imaging tools and assisting medical specialists. For example, image acquisition driven by Deep Learning Architecture may help optimise the scanning process and reshape the workflow with minimal patient intervention, ensuring the best security for imaging technicians. Furthermore, computer-aided platforms assist radiologists in making clinical decisions, such as disease identification, surveillance, and prognosis. In this workflow, we cover the full range of COVID-19-related medical imaging and analysis techniques, including image processing, segmentation, diagnosis, and follow-up. Traditional methods are used to interpret the evaluation, and various output metrics are collected.

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How to Cite
et. al., D. N. D. . (2021). A Deep Learning Neural Network Techniques in Visualization, Imaging Data Acquisition And Diagnosis for Covid-19 . Turkish Journal of Computer and Mathematics Education (TURCOMAT), 12(10), 3226–3239. Retrieved from https://turcomat.org/index.php/turkbilmat/article/view/4980
Section
Research Articles