Coronary artery segmentation is an essential procedure in the computer-aided diagnosis of coronary artery disease and enables further down-stream tasks eventually supporting CAD-RADS reporting. As a master student, your task will be to develop and evaluate innovative approaches for coronary artery segmentation from 3D CT data.
Your role:
Familiarize yourself with the topic and state of the art literature review
Familiarize yourself with available tooling and implement potentially required extensions for data curation, training environment, analysis tool preparation
Develop, implement and evaluate algorithm(s) for defined task incl. numerical experimentation on the local cluster and learning infrastructure iterating training, analysis, visualization, refinement
Write thesis and prepare a final presentation
Weekly interaction with supervisor, tight feedback loop including presentation of intermediate results
Potentially publication to high tier international conference (MICCAI/MIDL/SPIE/ISBI)
You're the right fit if:
You are a student in computer science, informatics, mathematics, physics.
You have knowledge in medical image processing.
Very good presentation and visualization skills.
You have comprehensive AI background and hands-on experience with recent NN architectures.
You have excellent programming skills (Python, PyTorch with C++ would be a strong plus).
You are proficient in the English language.
How we work together
We believe that we are better together than apart. For our office-based teams, this means working in-person at least 3 days per week.
This role is an office role.
About Philips
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If you’re interested in this role and have many, but not all, of the experiences needed, we encourage you to apply. You may still be the right candidate for this or other opportunities at Philips. Learn more about our commitment to diversity and inclusion here.
