Machine Learning-Based Analysis of Radiated vs. Non-Radiated Spheroids using OCT and Fluorescence Microscopy
- chair:Medical Imaging for Modeling and Simulation
- type:Master thesis
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The aim of this project is to investigate whether systematic differences can be detected between radiated and non-radiated 3D cell spheroids using advanced imaging techniques and machine learning. The student will expose spheroids to ionizing radiation and acquire data using Optical Coherence Tomography (OCT) and fluorescence microscopy. These imaging datasets will be preprocessed and analyzed using machine learning algorithms to identify patterns that distinguish between treated and untreated samples.