202 citations · 715 across the 48 of their papers we have counts for
4 papers · 1 filter
Amortized Normalizing Flows for Transcranial Ultrasound with Uncertainty Quantification
Rafael Orozco, Mathias Louboutin, Ali Siahkoohi +3
We present a novel approach to transcranial ultrasound computed tomography that utilizes normalizing flows to improve the speed of imaging and provide Bayesian uncertainty quantifi…
Memory Efficient Invertible Neural Networks for 3D Photoacoustic Imaging
Rafael Orozco, Mathias Louboutin, Felix J. Herrmann
Photoacoustic imaging (PAI) can image high-resolution structures of clinical interest such as vascularity in cancerous tumor monitoring. When imaging human subjects, geometric rest…
Learned imaging with constraints and uncertainty quantification
Felix J. Herrmann, Ali Siahkoohi, Gabrio Rizzuti
We outline new approaches to incorporate ideas from deep learning into wave-based least-squares imaging. The aim, and main contribution of this work, is the combination of handcraf…
Generalized Minkowski sets for the regularization of inverse problems
Bas Peters, Felix J. Herrmann
Many works on inverse problems in the imaging sciences consider regularization via one or more penalty functions or constraint sets. When the models/images are not easily described…