Bachelor Thesis : Accelerating dual-energy CT scan reconstruction using machine learning

An 11-week project exploring how machine learning accelerates dual-energy CT scan reconstruction. Using Python (PyTorch), an attention-based U-Net iteratively reconstructed images based on an existing algorithm. Building on experience with Jupyter Books, the project was documented in Markdown as an interactive article, embedding runnable Python notebooks. This format enhances reproducibility and collaboration in scientific computing.