26738 Intelligent Use of Artificial Intelligence to Advance Ultrasound-Based Cardiovascular Diagnosis
Begeleider(s): prof. dr. ir. Patrick Segers en prof. dr. Ernst Rietzschel

Richtingen: Master of Science in Computer Science Engineering


Echocardiography is the most widely utilized cardiac imaging modality. It can diagnose a variety of heart conditions. Furthermore, echocardiography can provide quantitative traits of key parameters of cardiac structure and function, including ventricular remodeling, atrial remodeling, valvular function and arterial function. Echocardiography is acquired in a typical fashion, following specific views of the heart. Previous echocardiography AI approaches have been limited by lack of detailed input information, lack of a stepwise logical approach to cardiac diagnosis and quantification, and limited sample sizes. Through a collaboration between UGent and UPenn, we propose to overcome these barriers and develop an AI platform for automatic echocardiographic feature detection, quantification and diagnosis. We will utilize existing datasets that have been quantified and/or segmented, that have been labeled carefully regarding specific views and/or that have been interpreted by expert clinicians. These datasets include:


Specific aims to pursue may include: