Image Analysis and Machine Learning for Medical Images

2021 Research Internship Project


Faculty Name

April Khademi

Project Title

Image Analysis and Machine Learning for Medical Images

Project Description

Medical images provide a glimpse of the internal state of the human body and relay information on the health and well-being of a subject. Radiology images, such as MRI, provide a gross description of disease, whereas digital pathology images describe disease on the cellular-level. Physicians must interpret these images, and render a diagnosis which is used for treatment planning. Unfortunately, human-based analysis is subjective, error-prone and inefficient, which ultimately reduces the quality of care for the patient. At the Image Analysis and Medicine Lab we are developing algorithms for neurological MRI and breast cancer digital pathology images to increase objectivity and efficiency of image interpretation to improve patient care. The student will be involved in software management, data management and algorithm development activities on these modalities.

Student Responsibility

The student will work on his/her own project, as well as with the other students to learn about image analysis and machine learning in medical imaging. Their own project will surround object detection using traditional machine learning or deep learning architectures for medical imaging.

Specific Requirements

Signals and Systems I and II

Application Procedure

To apply for this project you will need to login to the departmental web portal and select Research Internship from the sidebar menu.

Portal Login

April Khademi : Image Analysis and Machine Learning for Medical Images | Saturday March 27th 2021 07:50 AM