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

by   Carlos Rojas-Azabache, et al.

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.



page 1

page 2

page 3


Implementing a Detection System for COVID-19 based on Lung Ultrasound Imaging and Deep Learning

The COVID-19 pandemic started in China in December 2019 and quickly spre...

Point of Care Image Analysis for COVID-19

Early detection of COVID-19 is key in containing the pandemic. Disease d...

Adaptive Few-Shot Learning PoC Ultrasound COVID-19 Diagnostic System

This paper presents a novel ultrasound imaging point-of-care (PoC) COVID...

Lung Ultrasound Segmentation and Adaptation between COVID-19 and Community-Acquired Pneumonia

Lung ultrasound imaging has been shown effective in detecting typical pa...

Leveraging Multiple CNNs for Triaging Medical Workflow

High hospitalization rates due to the global spread of Covid-19 bring ab...

Multimodal Detection of COVID-19 Symptoms using Deep Learning Probability-based Weighting of Modes

The COVID-19 pandemic is one of the most challenging healthcare crises d...

Robotized Ultrasound Imaging of the Peripheral Arteries – a Phantom Study

The first choice in diagnostic imaging for patients suffering from perip...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.