Background
Regional nerve block is a common anaesthesia technique used for surgery on the extremities. A successful block requires excellent anaesthesia experience including the ability to identify the appropriate nerves and surrounding tissues on ultrasound and good skills with a needle.
Previous studies have primarily focussed on the usage of ultrasound which has shown that ultrasound increases the success rate of regional nerve blocks. Some studies, however, have found that even with ultrasound assistance, a relatively high failure rate persists. This failure rate has largely been attributed to operators with limited experience and insufficient ultrasound skills.
A failed nerve block not only results in a bad experience for the patient, it might even lead to damage to the patients’ health and in some cases complications could even threaten life.
It’s essential to recognise ultrasound anatomy when performing nerve blocks, however this may sometimes be hampered by patients’ habitus.
Tasks
In this project, the focus is on ultrasound images of the brachial plexus. The tasks are as follows:
- Develop an AI image segmentation application that correctly segments the brachial plexus on ultrasound images.
Requirements
- Students at the final year of a study in computer science, artificial intelligence, physics, or a related area.
- Basic level of knowledge and experience in Deep Learning in Healthcare
Information
- Project duration: 3 months
- Location: Radboud University Medical Center
- For more information, please contact Rob Tolboom
