Start date: 08-03-2021
End date: 17-12-2021
An abdominal aortic aneurysm (AAA) is a local enlargement of the abdominal artery. Patients with a AAA have an increased risk of rupture, often leading to death. It is therefore vital to early detect and closely monitor these patients. Detection and surveillance of AAA are currently performed by a specialist in the hospital, who measures the diameter of the AAA using ultrasound.
Ultrasound devices have recently become cheaper and portable. These portable devices can be connected to laptops, tablets and even smartphones, making them accessible for a wide range of users, including physicians in the first line.
In this project we will evaluate the use of a standardized sweep protocol using a low-cost ultrasound device that can be connected to a smartphone. The data that will be acquired with this protocol will be used to train a deep learning algorithm for automated measurement of the aorta diameter.
Development of deep learning algorithms that automatically determines the aortic diameter using a predefined ultrasound acquisition protocol.
When the algorithms have sufficient sensitivity and accuracy, and are able to run on a smartphone, they will be integrated in the current prototype.