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July 2025
Fine-Tuning Foundation Models for X-Ray Image Segmentation – MT Intro Talk by Maeen Abdelbadea Nasralla Alikarrar
Join us for an introductory presentation of a Master’s thesis focused on adapting foundation models for X-ray image segmentation. By fine-tuning the Segment Anything Model (SAM) using Low-Rank Adaptation (LoRA), this study aims to enhance its performance on X-ray images, addressing the domain gap between natural and medical imaging. The...
MA final talk Somali Roy: Generation of Artificial Vessel Trees for X-ray Image Analysis
Generation of Artificial Vessel Trees for X-ray Image Analysis Industry advisors: Dr. Peter Fischer, Dr. Michael Manhart, Dr. Fabiola Fernández-Gutiérrez University advisors: Prof. Dr.-Ing. habil. Andreas Maier, Florian Goldmann
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