Rapid deployment of AI-assisted COVID-19 detection for radiology

There is currently an abundance of research in the community in terms of capturing X-ray data around COVID-19 analysis to help diagnosis for radiologists. However, at the same time there are staffing shortages that lead either to long diagnosis wait times and potential misdiagnosis. Our research is focused around rapid deployment of AI and developing of a system to deploy AI technologies and algorithms using existing infrastructure within the hospital. Our proposed methodology uses existing hospital infrastructure while being able to take advantage of the AI models being developed to assist in COVID-19 diagnosis. For this purpose, we will develop advanced AI algorithms around COVID-19 detection for use with the system as well as X-ray image enhancing techniques that could potentially assist radiologists in making better decisions for diagnosis.

Faculty Supervisor:

Ali Sadeghi-Naini

Student:

Seyed Ali Jalalifar

Partner:

Pleora Technologies

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

York University