Detection of COVID-19 Disease using Deep Neural Networks with Ultrasound Imaging

2021/04/04 by C Rojas-Azabache, K Vilca-Janampa, Rojas-Azabache, Carlos +5
Medicine · #COVID-19 diagnosis using AI #Computer Vision and Pattern Recognition (cs.CV) #FOS: Computer and information sciences #FOS: Electrical engineering #Image and Video Processing (eess.IV) #Lung Cancer Diagnosis and Treatment #Ultrasound in Clinical Applications #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2104.01509

openalex publication_date 2021/04/04 · openalex created_date 2021/04/13 · openalex updated_date 2026/07/28

Abstract

The new coronavirus 2019 (COVID-2019) has rapidly become a pandemic and has had a devastating effect on both everyday life, public health and the global economy. It is critical to detect positive cases as early as possible to prevent the further spread of this epidemic and to treat affected patients quickly. The need for auxiliary diagnostic tools has increased as accurate automated tool kits are not available. This paper presents a work in progress that proposes the analysis of images of lung ultrasound scans using a convolutional neural network. The trained model will be used on a Raspberry Pi to predict on new images.

Citations

• Correlation of Chest CT and RT-PCR Testing for Coronavirus Disease 2019 (COVID-19) in China: A Report of 1014 Cases

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