Index
Machine-learning based localization of latest epicardial activation for cardiac resynchronization therapy guidance
Reinforcement Learning for the Planning of Liver Tumor Thermal Ablation
Adapting Pyro-NN with SPECT operators
Goal of this project is the implementation of the SPECT Forward and backward projection model in the Pyro-NN Framework. This would enable to include the SPECT reconstruction process into a Neural Network architecture.
Advancing the digital twin method
The aim of this research project was to develop a program that registers an XCAT phantom to a CT scan with a rigid and a non-rigid registration. The registered XCAT Phantom can be used to perform SPECT experiments and simulations without burdening the patient with an additional SPECT examination. To perform the registration the open source software Plastimatch version 1.8.0 was used. The results of the registration were evaluated visually and empirically. The registration was successful in most of the cases, but there were some cases where the rigid registration direction failed.