Automatic medical image/video segmentation, classification and analysis using machine learning

2021 Research Internship Project

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Faculty Name

Dafna Sussman

Project Title

Automatic medical image/video segmentation, classification and analysis using machine learning

Project Description

The Maternal-Fetal Imaging (MFI) Lab specializes in the development of non-invasive imaging techniques and image analysis for a variety of maternal, fetal, and placental conditions. Automatic analysis of medical images and medical videos using machine learning has been shown to facilitate early and rapid diagnosis and improvement in surgical techniques that can save the lives of expectant mothers and their babies.

Student Responsibility

The student will familiarize themselves with the current literature and prevalent machine learning architectures that have been developed for segmentation and classification techniques of medical images and videos. The student will then propose a novel architecture and use python programming to develop it to conduct the image and/or video analysis. They will work alongside BME graduate students and clinical collaborators.

Specific Requirements

1) Strong programming skills and experience with python programming, 2) Prior exposure to and basic understanding of machine learning, 3) Demonstrated problem solving, teamwork, and project management skills.