X-ray detectors in clinical computed tomography (CT) usually operate in current-integrating
mode. Their complicated signal statistics often lead to intractable likelihood functions for …

High-attenuation materials pose significant challenges to computed tomographic imaging.
Formed of high mass-density and high atomic number elements, they cause more severe …

Model-based image reconstruction (MBIR) for X-ray computed tomography (CT) offers
improved image quality and potential low-dose operation, but has yet to reach ubiquity in the …

This work addresses the resolution of penalized least-squares problems using the proximal
gradient algorithm (PGA). PGA can be accelerated by preconditioning strategies. However …

Model-based material decomposition is a statisticaliterative reconstruction framework where
basis material densityimages are estimated directly from spectral CT data. This methoduses …

A major challenge in X-ray computed tomography (CT) is reducing radiation dose while
maintaining high quality of reconstructed images. To reduce the radiation dose, one can …

With the recent introduction of CT scanners with large cone angles, wide coverage detectors
now provide a desirable scanning platform for cardiac CT that allows whole heart imaging in …

Splitting-based CT reconstruction algorithms decompose the reconstruction problem into a
iterated sequence of “easier” subproblems. One relatively memory-efficient algorithm …

X-ray detectors in clinical computed tomography (CT) operate in energy-integrating mode.
Their signal statistics is complicated by a cascade of random processes which prevent a …

The introduction of photon-counting detectors in x-ray computed tomography raises the
question of how reconstruction algorithms should be adapted to photon-counting …