Deep learning for medical image analysis
Project Description
This project aims to develop deep learning algorithms and image processing techniques for medical image analysis, including various medical image modalities such as computed tomography (CT), x-ray, magnetic resonance imaging (MRI), whole-slide pathology, fundus, Optical Coherence Tomography (OCT) and Optical Coherence Tomography Angiography (OCTA), etc.
Students are also encouraged to propose their new ideas within the scope of this topic. Topics of mutual interests can be flexible. High-quality research papers are expected if possible.
Students are also encouraged to propose their new ideas within the scope of this topic. Topics of mutual interests can be flexible. High-quality research papers are expected if possible.
Supervisor
CHEN, Hao
Quota
5
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP3200
UROP4100
Applicant's Roles
Develop algorithms and draft papers.
Applicant's Learning Objectives
Grasp deep learning techniques; Publish high-quality research papers if possible.
Complexity of the project
Moderate