367 citations · 406 across the 13 of their papers we have counts for
4 papers · 1 filter
Unsupervised denoising for sparse multi-spectral computed tomography
Satu I. Inkinen, Mikael A. K. Brix, Miika T. Nieminen +2
Multi-energy computed tomography (CT) with photon counting detectors (PCDs) enables spectral imaging as PCDs can assign the incoming photons to specific energy channels. However, P…
Robust Data-Driven Accelerated Mirror Descent
Hong Ye Tan, Subhadip Mukherjee, Junqi Tang +2
Learning-to-optimize is an emerging framework that leverages training data to speed up the solution of certain optimization problems. One such approach is based on the classical mi…
Sparsity promoting reconstructions via hierarchical prior models in diffuse optical tomography
Anssi Manninen, Meghdoot Mozumder, Tanja Tarvainen +1
Diffuse optical tomography (DOT) is a severely ill-posed nonlinear inverse problem that seeks to estimate optical parameters from boundary measurements. In the Bayesian framework,…
Learned reconstruction methods with convergence guarantees
Subhadip Mukherjee, Andreas Hauptmann, Ozan Öktem +2
In recent years, deep learning has achieved remarkable empirical success for image reconstruction. This has catalyzed an ongoing quest for precise characterization of correctness a…