  The rapid and seemingly endless expansion of COVID-19 can be traced back to
the inefficiency and shortage of testing kits that offer accurate results in a
timely manner. An emerging popular technique, which adopts improvements made in
mobile ultrasound technology, allows for healthcare professionals to conduct
rapid screenings on a large scale. We present an image-based solution that aims
at automating the testing process which allows for rapid mass testing to be
conducted with or without a trained medical professional that can be applied to
rural environments and third world countries. Our contributions towards rapid
large-scale testing include a novel deep learning architecture capable of
analyzing ultrasound data that can run in real-time and significantly improve
the current state-of-the-art detection accuracies using image-based COVID-19
detection.
