MSc Thesis: Super-Resolution MRI Guided by Cardiac Scout Imaging
Background
In cardiac MRI protocols, low-resolution non-diagnostic scout scans are typically acquired prior to the more detailed, diagnostic cardiac cine MRI sequences. Although these scout images are static (i.e., possessing no temporal information) and exhibit lower overall image quality, they provide a better 3D overview of the heart when compared to conventional cardiac cine MRI. This project aims to explore super-resolution techniques to reconstruct high-quality 2D and potentially 3D cardiac views from these scout scans. The goal is to bridge the quality gap between scout and cine acquisitions, potentially enabling faster or even scout-only cardiac imaging pipelines in the future.
Your tasks
- Investigate and compare state-of-the-art super-resolution techniques
- Work with real-world cardiac MRI data
- Explore clinical relevance and reconstruction fidelity metrics
What we offer
- Access to a new dataset of clinical cardiac scout scans
- Realisitc compute ressources
- Opportunity to contribute to ongoing research and potential publication in medical imaging journals/conferences.
- Exposure to cutting-edge AI tools and frameworks for 3D medical image generation.
Details
The student will first explore the landscape of superresolution and generative models. After concepting the core tasks involves implementing a model for scout bases superresoltuon. Evaluation will be done using ground truth cine data at hand.
References
Wang, Shuo, et al. "Joint motion correction and super resolution for cardiac segmentation via latent optimisation." International Conference on Medical Image Computing and Computer-Assisted Intervention. Cham: Springer International Publishing, 2021.
He, Xiaoxiao, et al. "Dmcvr: Morphology-guided diffusion model for 3d cardiac volume reconstruction." International conference on medical image computing and computer-assisted intervention. Cham: Springer Nature Switzerland, 2023.