Multi-modal Image Registration for Challenging Task
Open Master Thesis
Contact person: Bailiang Jian, Morteza Ghahremani [morteza.ghahremani@tum.de], Christian Wachinger
This master’s thesis project offers an exciting opportunity to develop cutting-edge AI methods for multi-modal medical image registration. The research will focus on advanced techniques for aligning challenging image pairs from different modalities, such as ultrasound with MRI or microscopy images with different contrast characteristics.
What sets you apart:
- Master’s student in Computer Science, Medical Physics, or related field
- Strong programming skills in Python and deep expertise with PyTorch
- A good understanding of mathematics, deep learning, and computer vision.
- Preferred: Experience in image registration or optical flow estimation
- Passionate about solving complex medical imaging challenges
Duration: 6 months
We look forward to receiving your application with a short statement of motivation, your transcript report, and your CV.