Medical Imaging Domain-Expertise Machine Learning for Interrogation of COVID

The COVID-19 pandemic represents a pressing public health need for computational techniques to augment the interpretation of medical images in their role for: 1) surveillance, detection, and triaging of COVID-19 medical images given potential resurgence; 2) differential diagnosis of COVID-19 patients; and 3)prognosis, as well as prediction and monitoring of treatment response, to help in patient management. While thoracic imaging, including chest radiography and computed tomography (CT), are being re-examined for their role in patient management, the limitations for improved interpretation are partially due to the qualitative interpretation of the images, and thus this project's aim is to develop machine intelligence methods to aid in the interrogation of medical images from COVID-19 patients. Successful completion of the research will demonstrate cascade-based deep transfer learning between similar but different thoracic disease states (e.g., interstitial diseases to COVID-19) and a clinical tool to aid in the triaging of COVID-19 patients in terms of detection, treatment planning, and monitoring.