no code implementations • 1 Feb 2023 • Tao Ge, Maria Medrano, Rui Liao, David G. Politte, Jeffrey F. Williamson, Bruce R. Whiting, Joseph A. O'Sullivan
Therefore, to improve its convergence, we have embedded DECT SIR into a deep learning model-based unrolled network for 3D DECT reconstruction (MB-DECTNet) that can be trained in an end-to-end fashion.
no code implementations • 31 Jan 2022 • Tao Ge, Maria Medrano, Rui Liao, Jeffrey F. Williamson, David G. Politte, Bruce R. Whiting, Joseph A. O'Sullivan
We compared DEAM with the proposed method to the original DEAM and vendor reconstructions with and without metal-artifact reduction for orthopedic implants (O-MAR).
no code implementations • 30 Jul 2021 • Tao Ge, Maria Medrano, Rui Liao, David G. Politte, Jeffrey F. Williamson, Joseph A. O'Sullivan
Dual-energy CT (DECT) has been widely investigated to generate more informative and more accurate images in the past decades.
no code implementations • 25 Jun 2020 • Michael R. Walker II, Joseph A. O'Sullivan
Transmission measurements resolve low-frequency ambiguity in the joint image estimation problem, while multiple scatter measurements resolve the attenuation image.
no code implementations • 26 Oct 2017 • Jingwei Lu, David G. Politte, Joseph A. O'Sullivan
In the classic sparsity-driven problems, the fundamental L-1 penalty method has been shown to have good performance in reconstructing signals for a wide range of problems.
no code implementations • 29 Jan 2016 • Ikenna Odinaka, Joseph A. O'Sullivan, David G. Politte, Kenneth P. MacCabe, Yan Kaganovsky, Joel A. Greenberg, Manu Lakshmanan, Kalyani Krishnamurthy, Anuj Kapadia, Lawrence Carin, David J. Brady
In x-ray coherent scatter tomography, tomographic measurements of the forward scatter distribution are used to infer scatter densities within a volume.
no code implementations • 29 Jan 2016 • Ikenna Odinaka, Yan Kaganovsky, Joel A. Greenberg, Mehadi Hassan, David G. Politte, Joseph A. O'Sullivan, Lawrence Carin, David J. Brady
We pursue an optimization transfer approach where convex decompositions are used to lift the problem such that all hyper-voxels can be updated in parallel and in closed-form.
no code implementations • 24 Jun 2015 • S. Degirmenci, Joseph A. O'Sullivan, David G. Politte
As the iterations proceed, the wavelet tree on which the updates are made is expanded based on a criterion and detail coefficients at each level are updated and the tree is expanded this way.
1 code implementation • 29 Dec 2014 • Yan Kaganovsky, Shaobo Han, Soysal Degirmenci, David G. Politte, David J. Brady, Joseph A. O'Sullivan, Lawrence Carin
We propose a globally convergent alternating minimization (AM) algorithm for image reconstruction in transmission tomography, which extends automatic relevance determination (ARD) to Poisson noise models with Beer's law.