The atrial substrate undergoes electrical and structural remodeling during atrial fibrillation. Detailed multiscale models were used to study the effect of structural remodeling induced at the cellular and tissue levels. Simulated electrograms were used to train a machine-learning algorithm to characterize the substrate. Also, wave propagation direction was tracked from unannotated electrograms. In conclusion, in silico experiments provide insight into electrograms' information of the substrate.

Intraoperative Gamma Cameras are becoming increasingly common for radio-guided surgery. Coded Aperture Imaging has been proposed as a collimation technique, because it offers a better trade-off between sensitivity and spatial resolution, but requires image reconstruction. Therefore, a Convolutional Encoder-Decoder Network was developed and quantitatively compared with analytical methods. Furthermore, 3D-localization of point-like sources was investigated.