13 citations · 23 across the 9 of their papers we have counts for
10 papers
MB-DECTNet: A Model-Based Unrolled Network for Accurate 3D DECT Reconstruction
Tao Ge, Maria Medrano, Rui Liao +4
Numerous dual-energy CT (DECT) techniques have been developed in the past few decades. Dual-energy CT (DECT) statistical iterative reconstruction (SIR) has demonstrated its potenti…
A Metal Artifact Reduction Scheme For Accurate Iterative Dual-Energy CT Algorithms
Tao Ge, Maria Medrano, Rui Liao +4
CT images have been used to generate radiation therapy treatment plans for more than two decades. Dual-energy CT (DECT) has shown high accuracy in estimating electronic density or…
A Machine-learning Based Initialization for Joint Statistical Iterative Dual-energy CT with Application to Proton Therapy
Tao Ge, Maria Medrano, Rui Liao +3
Dual-energy CT (DECT) has been widely investigated to generate more informative and more accurate images in the past decades. For example, Dual-Energy Alternating Minimization (DEA…
Highly accurate model for prediction of lung nodule malignancy with CT scans
Jason Causey, Junyu Zhang, Shiqian Ma +6
Computed tomography (CT) examinations are commonly used to predict lung nodule malignancy in patients, which are shown to improve noninvasive early diagnosis of lung cancer. It rem…
Laplacian Prior Variational Automatic Relevance Determination for Transmission Tomography
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. However…
Stochastic First-Order Minimization Techniques Using Jensen Surrogates for X-Ray Transmission Tomography
Soysal Degirmenci, Joseph A. O'Sullivan, David G. Politte
Image reconstruction in X-ray transmission tomography has been an important research field for decades. In light of data volume increasing faster than processor speeds, one needs a…