activity
20122026
most citedCUQIpy: I. Computational uncertainty quantification for inverse problems in Python

13 citations · 28 across the 10 of their papers we have counts for

collaborators
Showing 2021Show all

5 papers · 1 filter

math.NA2021

Stopping Rules for Algebraic Iterative Reconstruction Methods in Computed Tomography

Per Christian Hansen, Jakob Sauer Jørgensen, Peter Winkel Rasmussen

Algebraic models for the reconstruction problem in X-ray computed tomography (CT) provide a flexible framework that applies to many measurement geometries. For large-scale problems…

physics.med-ph2021

Enhanced hyperspectral tomography for bioimaging by spatiospectral reconstruction

Ryan Warr, Evelina Ametova, Robert J. Cernik +6

Here we apply hyperspectral bright field imaging to collect computed tomographic images with excellent energy resolution (800 eV), applying it for the first time to map the distrib…

physics.med-ph2021

Crystalline phase discriminating neutron tomography using advanced reconstruction methods

Evelina Ametova, Genoveva Burca, Suren Chilingaryan +8

Time-of-flight neutron imaging offers complementary attenuation contrast to X-ray computed tomography (CT), coupled with the ability to extract additional information from the vari…

physics.med-ph2021

Core Imaging Library -- Part II: Multichannel reconstruction for dynamic and spectral tomography

Evangelos Papoutsellis, Evelina Ametova, Claire Delplancke +7

The newly developed Core Imaging Library (CIL) is a flexible plug and play library for tomographic imaging with a specific focus on iterative reconstruction. CIL provides building…

math.OC2021

Core Imaging Library -- Part I: a versatile Python framework for tomographic imaging

Jakob S. Jørgensen, Evelina Ametova, Genoveva Burca +8

We present the Core Imaging Library (CIL), an open-source Python framework for tomographic imaging with particular emphasis on reconstruction of challenging datasets. Conventional…