Project Description:

Duchenne Muscular Dystrophy (DMD) is a progressive, recessive neuromuscular disorder that primarily affects boys. Cardiovascular complications are the leading cause of mortality in these patients, making early detection of cardiac dysfunction essential for timely intervention with cardioprotective therapies.

This project aims to improve the diagnosis and monitoring of cardiac disease in muscular dystrophies such as DMD by developing software capable of analyzing imaging data from multiple modalities, including 4D (3D + time) ultrasound and magnetic resonance imaging (MRI). The framework integrates cardiac strain analysis and machine learning models for ventricle segmentation and mortality risk prediction. By providing clinicians with advanced diagnostic tools and enabling more sophisticated research into cardiovascular mechanics, this work seeks to facilitate early intervention and enhance our understanding of disease progression. Students assisting with this project would be working on the development of medical image analysis software.

Tasks include designing graphical user interfaces for end-users, creating image analysis scripts and developing machine learning models such as convolutional neural networks for image segmentation and disease progression prediction.

Requirements:

Students should be interested in imaging research. Previous programming experience is required, although proficiency in a specific language or framework is not mandatory. A basic understanding of cardiovascular anatomy will be helpful but is not necessary.