187 citations · 705 across the 37 of their papers we have counts for
6 papers · 1 filter
RSR-NF: Neural Field Regularization by Static Restoration Priors for Dynamic Imaging
Berk Iskender, Sushan Nakarmi, Nitin Daphalapurkar +2
Dynamic imaging involves the reconstruction of a spatio-temporal object at all times using its undersampled measurements. In particular, in dynamic computed tomography (dCT), only…
RED-PSM: Regularization by Denoising of Factorized Low Rank Models for Dynamic Imaging
Berk Iskender, Marc L. Klasky, Yoram Bresler
Dynamic imaging addresses the recovery of a time-varying 2D or 3D object at each time instant using its undersampled measurements. In particular, in the case of dynamic tomography,…
Dynamic Tomography Reconstruction by Projection-Domain Separable Modeling
Berk Iskender, Marc L. Klasky, Yoram Bresler
In dynamic tomography the object undergoes changes while projections are being acquired sequentially in time. The resulting inconsistent set of projections cannot be used directly…
A Set-Theoretic Study of the Relationships of Image Models and Priors for Restoration Problems
Bihan Wen, Yanjun Li, Yuqi Li +1
Image prior modeling is the key issue in image recovery, computational imaging, compresses sensing, and other inverse problems. Recent algorithms combining multiple effective prior…
Composition-Aware Spectroscopic Tomography
Luke Pfister, Rohit Bhargava, Yoram Bresler +1
Chemical imaging provides information about the distribution of chemicals within a target. When combined with structural information about the target, in situ chemical imaging open…
Transform Learning for Magnetic Resonance Image Reconstruction: From Model-based Learning to Building Neural Networks
Bihan Wen, Saiprasad Ravishankar, Luke Pfister +1
Magnetic resonance imaging (MRI) is widely used in clinical practice, but it has been traditionally limited by its slow data acquisition. Recent advances in compressed sensing (CS)…