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Imaging in Nuclear Medicine

Medical Physics, 2016-06, Vol.43 (6), p.3207-3207

Palmer, Matthew

2016

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Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registrationa

Medical physics (Lancaster), 2008-09, Vol.35 (9), p.3998-4011

2008

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TH-EF-BRA-03: Assessment of Data-Driven Respiratory Motion-Compensation Methods for 4D-CBCT Image Registration and Reconstruction Using Clinical Datasets

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3897-3897

2016

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SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3388-3388

2016

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90Y ‐PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

Medical physics (Lancaster), 2015-07, Vol.42 (7), p.4295-4309

2015

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WE-FG-207B-09: Experimental Assessment of Noise and Spatial Resolution in Virtual Non-Contrast Dual-Energy CT Images Across Multiple Patient Sizes and CT Systems

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3836-3836

2016

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SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3345-3345

2016

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TH‐CD‐303‐07: Evaluation of Four Data‐Driven Respiratory Motion‐Compensation Methods for Four‐Dimensional Cone‐Beam CT Registration and Reconstruction

Medical physics (Lancaster), 2015-06, Vol.42 (6Part43), p.3730-3730

2015

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TU-D-207A-01: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3747-3748

Leng, S.

2016

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TU-D-207A-00: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3747-3748

2016

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TU-D-207A-03: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3747-3748

Li, K.

2016

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TU-D-207A-02: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3747-3748

Samei, E.

2016

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SU-G-206-10: Low-Contrast Detectability Vs. Dose for CT Images Reconstructed Using Filtered Backprojection and Iterative Reconstruction: Assessment with a Model Observer

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3641-3641

2016

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WE‐G‐207‐03: Mask Guided Image Reconstruction (MGIR): A Novel Method for Ultra‐Low‐Dose 3D and Enhanced 4D Cone‐Beam Computer‐Tomography

Medical physics (Lancaster), 2015-06, Vol.42 (6Part41), p.3696-3696

2015

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TU‐EF‐204‐04: Feasibility Study of a Novel Stationary Spectral CT Scanner

Medical physics (Lancaster), 2015-06, Vol.42 (6Part34), p.3620-3621

2015

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Erratum: “Three‐dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F‐18‐FDG PET” [Med. Phys. 41(12), 121904 (2014)]

Medical physics (Lancaster), 2015-08, Vol.42 (8), p.4998-4998

2015

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TU‐F‐CAMPUS‐I‐05: Parameterization of the Noise Power Spectrum in X‐Ray Computed Tomography

Medical physics (Lancaster), 2015-06, Vol.42 (6Part36), p.3643-3643

2015

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SU‐E‐J‐108: Solving the Chinese Postman Problem for Effective Contour Deformation

Medical physics (Lancaster), 2015-06, Vol.42 (6Part8), p.3289-3289

2015

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WE‐G‐207‐05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

Medical physics (Lancaster), 2015-06, Vol.42 (6Part41), p.3697-3697

2015

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TU‐EF‐204‐12: Quantitative Evaluation of Spectral Detector CT Using Virtual Monochromatic Images: Initial Results

Medical physics (Lancaster), 2015-06, Vol.42 (6Part34), p.3622-3623

2015

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SU‐E‐I‐12: Flexible Geometry Computed Tomography

Medical physics (Lancaster), 2015-06, Vol.42 (6Part5), p.3244-3244

Shaw, R

2015

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SU‐E‐I‐13: Evaluation of Metal Artifact Reduction (MAR) Software On Computed Tomography (CT) Images

Medical physics (Lancaster), 2015-06, Vol.42 (6Part5), p.3244-3244

2015

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TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3890-3891

2016

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SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3415-3415

2016

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SU-F-I-54: Spatial Resolution Studies in Proton CT Using a Phase-II Prototype Head Scanner

Medical physics (Lancaster), 2016-06, Vol.43 (6), p.3399-3399

2016

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Imaging in Nuclear Medicine

Reconstruction of a time-averaged midposition CT scan for radiotherapy planning of lung cancer patients using deformable registrationa

TH-EF-BRA-03: Assessment of Data-Driven Respiratory Motion-Compensation Methods for 4D-CBCT Image Registration and Reconstruction Using Clinical Datasets

SU-F-I-08: CT Image Ring Artifact Reduction Based On Prior Image

90Y ‐PET imaging: Exploring limitations and accuracy under conditions of low counts and high random fraction

WE-FG-207B-09: Experimental Assessment of Noise and Spatial Resolution in Virtual Non-Contrast Dual-Energy CT Images Across Multiple Patient Sizes and CT Systems

SU-D-206-03: Segmentation Assisted Fast Iterative Reconstruction Method for Cone-Beam CT

TH‐CD‐303‐07: Evaluation of Four Data‐Driven Respiratory Motion‐Compensation Methods for Four‐Dimensional Cone‐Beam CT Registration and Reconstruction

TU-D-207A-01: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

TU-D-207A-00: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

TU-D-207A-03: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

TU-D-207A-02: Quantitative Assessment of CT Systems with Iterative Image Reconstruction Algorithms

SU-G-206-10: Low-Contrast Detectability Vs. Dose for CT Images Reconstructed Using Filtered Backprojection and Iterative Reconstruction: Assessment with a Model Observer

WE‐G‐207‐03: Mask Guided Image Reconstruction (MGIR): A Novel Method for Ultra‐Low‐Dose 3D and Enhanced 4D Cone‐Beam Computer‐Tomography

TU‐EF‐204‐04: Feasibility Study of a Novel Stationary Spectral CT Scanner

Erratum: “Three‐dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F‐18‐FDG PET” [Med. Phys. 41(12), 121904 (2014)]

TU‐F‐CAMPUS‐I‐05: Parameterization of the Noise Power Spectrum in X‐Ray Computed Tomography

SU‐E‐J‐108: Solving the Chinese Postman Problem for Effective Contour Deformation

WE‐G‐207‐05: Relationship Between CT Image Quality, Segmentation Performance, and Quantitative Image Feature Analysis

TU‐EF‐204‐12: Quantitative Evaluation of Spectral Detector CT Using Virtual Monochromatic Images: Initial Results

SU‐E‐I‐12: Flexible Geometry Computed Tomography

SU‐E‐I‐13: Evaluation of Metal Artifact Reduction (MAR) Software On Computed Tomography (CT) Images

TH-CD-207B-09: Task-Driven Fluence Field Modulation Design for Model-Based Iterative Reconstruction in CT

SU-F-J-41: Experimental Validation of a Cascaded Linear System Model for MVCBCT with a Multi-Layer EPID

SU-F-I-54: Spatial Resolution Studies in Proton CT Using a Phase-II Prototype Head Scanner

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