Master thesis done in Computer Vision Group of Technical University of Munich. Supervisors are Dr. Yvain Queau and Prof. Daniel Cremers.

Traditional Image Processing Techniques for Nailfold Capillary Detection: A project showcasing a non-ML/DL approach to detect and count nailfold capillaries, emphasizing the application of fundamental image analysis methods in medical diagnostics.

This repository presents exercises related to magnetic resonance imaging (MRI) and an introduction to quantitative magnetic resonance imaging (qMRI).

Classification project using Self-Organizing Maps (SOM) to differentiate patients and healthy subjects from marker data, encompassing network construction, training, and testing phases.

Solutions for Advanced Image Analysis course assignments, featuring model designs for image summation and generation with MNIST, and style transfer using CycleGAN with MNIST and SVHN datasets.