• EE 296 Sophomore Projects
• EE 396 Junior Projects
• EE 496 Senior Projects

AI Based COVID-19 Detection Using Chest CT Scans

Courses: • EE 496 Senior Projects • EE 396 Junior Projects

Prerequisites: Consent of instructor (see preferred skills and knowledge below)

Description: This is a collaborative project with the Queen's Medical Center (QMC) at Hawaii. The goal of this project is to develop artificial intelligence (AI) systems to detect COVID-19 viral infection using chest X-ray computational tomography (CT) scans.

Potential approaches include combinations of state-of-the-art deep learning methods,

• object detection neural network (NN), e.g., YOLOv3,


• image segmentation NN, e.g., DeepLabv3, or


• image recognition NN, e.g., ResNet-101.

We will use an open-access benchmark COVID-19 CT dataset to train developed AI systems, and test to CT scans collected from QMC.



Preferred skills and knowledge include

• Python or MATLAB programming skills (e.g., reading, understanding, and writing codes)
• some knowledge in linear algebra (e.g., EE345 and MATH307/311) and probability theory and statistics (e.g., EE342)

If you have taken EE416: Intro. Image Processing and Computer Vision or plan to take it, that would be extremely helpful!

Focus: O (Oral) W (Writing)

Advisor: Il Yong Chun | iychun@hawaii.edu

Project Web Site: