CoRSAI: A System for Robust Interpretation of CT Scans of COVID-19 Patients Using Deep Learning

Abstract

Analysis of chest CT scans can be used in detecting parts of lungs that are affected by infectious diseases such as COVID-19. Determining the volume of lungs affected by lesions is essential for formulating treatment recommendations and prioritizing patients by severity of the disease. In this paper we adopted an approach based on using an ensemble of deep convolutional neural networks for segmentation of slices of lung CT scans. Using our models we are able to segment the lesions, evaluate patients dynamics, estimate relative volume of lungs affected by lesions and evaluate the lung damage stage. Our models were trained on data from different medical centers. We compared predictions of our models with those of six experienced radiologists and our segmentation model outperformed most of them. On the task of classification of disease severity, our model outperformed all the radiologists. CCS Concepts: • Applied computing → Health care information systems; • Computing methodologies → Computer vision; Ensemble methods.

Project Achoo: A Practical Model and Application for COVID-19 Detection from Recordings of Breath, Voice, and Cough

“…The application is implemented in client-server manner with iOS / Android UI frontend and server-side storage and computational backend, implemented in Flask. 2 The trained deep convolutional networks are converted into ONNX format 3 and operate in inference mode using the ONNX Runtime 4 library for optimal throughput. During each user session the client app collects the data (symptoms, samples of cough, breath and voice) and sends it to the server, which processes it, applies the models and yields the response.…”

“…All these reasons have led machine learning researchers to develop diagnostic methods that exploit visual information, such as chest X-ray images, computer tomography, or ultrasound studies (see references in [1]). Great progress has been made due to the large amount of data available to researchers, and now many clinics around the world use image based automated methods to help patients with COVID [2].…”