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Learning to Reconstruct Computed Tomography Images Directly From Sinogram Data Under A Variety of Data Acquisition Conditions

IEEE transactions on medical imaging, 2019-10, Vol.38 (10), p.2469-2481

2019

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Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

Medical physics (Lancaster), 2008-02, Vol.35 (2), p.660-663

2008

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Experimental measurement of local noise power spectrum (NPS) in photon counting detector‐CT (PCD‐CT) using a single data acquisition

Medical physics (Lancaster), 2024-05, Vol.51 (6), p.4081-4094

2024

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Noise power spectrum (NPS) in computed tomography: Enabling local NPS measurement without stationarity and ergodicity assumptions

Medical physics (Lancaster), 2024-07, Vol.51 (7), p.4655-4672

2024

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Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Medical physics (Lancaster), 2014-04, Vol.41 (4), p.041906-n/a

2014

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Accurate and robust sparse‐view angle CT image reconstruction using deep learning and prior image constrained compressed sensing (DL‐PICCS)

Medical physics (Lancaster), 2021-10, Vol.48 (10), p.5765-5781

2021

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Deep‐Interior: A new pathway to interior tomographic image reconstruction via a weighted backprojection and deep learning

Medical physics (Lancaster), 2024-02, Vol.51 (2), p.946-963

2024

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Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging

Medical physics (Lancaster), 2023-10, Vol.50 (10), p.6022-6035

2023

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Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

Medical physics (Lancaster), 2014-07, Vol.41 (7), p.071911-n/a

2014

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Dual Energy Differential Phase Contrast CT (DE-DPC-CT) Imaging

IEEE transactions on medical imaging, 2020-11, Vol.39 (11), p.3278-3289

2020

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Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence

Radiology, 2021-02, Vol.298 (2), p.E88-E97

2021

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Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

Physics in medicine & biology, 2009-10, Vol.54 (19), p.5781-5804

2009

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Statistical properties of cerebral CT perfusion imaging systems. Part II. Deconvolution‐based systems

Medical physics (Lancaster), 2019-11, Vol.46 (11), p.4881-4897

2019

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Synchronized multiartifact reduction with tomographic reconstruction (SMART‐RECON): A statistical model based iterative image reconstruction method to eliminate limited‐view artifacts and to mitigate the temporal‐average artifacts in time‐resolved CT

Medical physics (Lancaster), 2015-08, Vol.42 (8), p.4698-4707

2015

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Quantitative lung perfusion blood volume using dual energy CT–based effective atomic number (Zeff) imaging

Medical physics (Lancaster), 2021-11, Vol.48 (11), p.6658-6672

2021

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Prior image constrained compressed sensing: Implementation and performance evaluation

Medical physics (Lancaster), 2012-01, Vol.39 (1), p.66-80

2012

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Reconstruction of three‐dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning

Medical physics (Lancaster), 2022-02, Vol.49 (2), p.901-916

2022

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A quality‐checked and physics‐constrained deep learning method to estimate material basis images from single‐kV contrast‐enhanced chest CT scans

Medical physics (Lancaster), 2023-06, Vol.50 (6), p.3368-3388

2023

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Is high sensitivity always desirable for a grating‐based differential phase contrast imaging system?

Medical physics (Lancaster), 2020-03, Vol.47 (3), p.1215-1228

2020

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High Pitch Helical CT Reconstruction

IEEE transactions on medical imaging, 2021-11, Vol.40 (11), p.3077-3088

2021

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An Empirical Data Inconsistency Metric (DIM) Driven CT Image Reconstruction Method

IEEE transactions on medical imaging, 2019-02, Vol.38 (2), p.337-348

2019

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Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction

Medical physics (Lancaster), 2013-02, Vol.40 (2), p.021902-n/a

2013

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Reduced anatomical clutter in digital breast tomosynthesis with statistical iterative reconstruction

Medical physics (Lancaster), 2018-05, Vol.45 (5), p.2009-2022

2018

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Grating based x-ray differential phase contrast imaging without mechanical phase stepping

Optics express, 2014-06, Vol.22 (12), p.14246-14252

2014

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Statistical properties of cerebral CT perfusion imaging systems. Part I. Cerebral blood volume maps generated from nondeconvolution‐based systems

Medical physics (Lancaster), 2019-11, Vol.46 (11), p.4869-4880

2019

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Learning to Reconstruct Computed Tomography Images Directly From Sinogram Data Under A Variety of Data Acquisition Conditions

Prior image constrained compressed sensing (PICCS): A method to accurately reconstruct dynamic CT images from highly undersampled projection data sets

Experimental measurement of local noise power spectrum (NPS) in photon counting detector‐CT (PCD‐CT) using a single data acquisition

Noise power spectrum (NPS) in computed tomography: Enabling local NPS measurement without stationarity and ergodicity assumptions

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Accurate and robust sparse‐view angle CT image reconstruction using deep learning and prior image constrained compressed sensing (DL‐PICCS)

Deep‐Interior: A new pathway to interior tomographic image reconstruction via a weighted backprojection and deep learning

Correcting statistical CT number biases without access to raw detector counts: Applications to high spatial resolution photon counting CT imaging

Statistical model based iterative reconstruction (MBIR) in clinical CT systems. Part II. Experimental assessment of spatial resolution performance

Dual Energy Differential Phase Contrast CT (DE-DPC-CT) Imaging

Diagnosis of Coronavirus Disease 2019 Pneumonia by Using Chest Radiography: Value of Artificial Intelligence

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

Statistical properties of cerebral CT perfusion imaging systems. Part II. Deconvolution‐based systems

Synchronized multiartifact reduction with tomographic reconstruction (SMART‐RECON): A statistical model based iterative image reconstruction method to eliminate limited‐view artifacts and to mitigate the temporal‐average artifacts in time‐resolved CT

Quantitative lung perfusion blood volume using dual energy CT–based effective atomic number (Zeff) imaging

Prior image constrained compressed sensing: Implementation and performance evaluation

Reconstruction of three‐dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning

A quality‐checked and physics‐constrained deep learning method to estimate material basis images from single‐kV contrast‐enhanced chest CT scans

Is high sensitivity always desirable for a grating‐based differential phase contrast imaging system?

High Pitch Helical CT Reconstruction

An Empirical Data Inconsistency Metric (DIM) Driven CT Image Reconstruction Method

Characterization of statistical prior image constrained compressed sensing (PICCS): II. Application to dose reduction

Reduced anatomical clutter in digital breast tomosynthesis with statistical iterative reconstruction

Grating based x-ray differential phase contrast imaging without mechanical phase stepping

Statistical properties of cerebral CT perfusion imaging systems. Part I. Cerebral blood volume maps generated from nondeconvolution‐based systems

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