COVID-19 can be traced back to the inefficiency and shortage of testing kits that offer accurate results in atimely manner . We present an image-based solution that aimsat automating the testing process which allows for rapid mass testing to beconducted with or without a trained medical professional that can be applied torural environments and third world countries . Our contributions towards rapidlarge-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 accuracy .

Author(s) : Shehan Perera, Srikar Adhikari, Alper Yilmaz

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Keywords : testing - detection - architecture - ultrasound - covid -

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