Works matching IS 23791381 AND DT 2020 AND VI 6 AND IP 2
Results: 26
Diffusion-Weighted and Dynamic Contrast-Enhanced MRI Derived Imaging Metrics for Stereotactic Body Radiotherapy of Pancreatic Ductal Adenocarcinoma: Preliminary Findings.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 261, doi. 10.18383/j.tom.2020.00015
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Deep Feature Stability Analysis Using CT Images of a Physical Phantom Across Scanner Manufacturers, Cartridges, Pixel Sizes, and Slice Thickness.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 250, doi. 10.18383/j.tom.2020.00003
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4D-CT Attenuation Correction in Respiratory-Gated PET for Hypoxia Imaging: Is It Really Beneficial?
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 241, doi. 10.18383/j.tom.2019.00027
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Diffusion-Weighted Echo Planar Imaging using MUltiplexed Sensitivity Encoding and Reverse Polarity Gradient in Head and Neck Cancer: An Initial Study.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 231, doi. 10.18383/j.tom.2020.00014
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Radiomics Prediction of EGFR Status in Lung Cancer--Our Experience in Using Multiple Feature Extractors and The Cancer Imaging Archive Data.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 223, doi. 10.18383/j.tom.2020.00017
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Tumor Sphericity Predicts Response in Neoadjuvant Chemotherapy for Invasive Breast Cancer.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 216, doi. 10.18383/j.tom.2020.00016
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Lung Nodule Sizes Are Encoded When Scaling CT Image for CNN's.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 209, doi. 10.18383/j.tom.2019.00024
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Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 203, doi. 10.18383/j.tom.2020.00012
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Intraobserver Variability in Bladder Cancer Treatment Response Assessment With and Without Computerized Decision Support.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 194, doi. 10.18383/j.tom.2020.00013
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A Fully Automated Deep Learning Network for Brain Tumor Segmentation.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 186, doi. 10.18383/j.tom.2019.00026
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Computational Modeling of Interstitial Fluid Pressure and Velocity in Head and Neck Cancer Based on Dynamic Contrast-Enhanced Magnetic Resonance Imaging: Feasibility Analysis.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 129, doi. 10.18383/j.tom.2020.00005
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Quantitative Comparison of Prone and Supine PERCIST Measurements in Breast Cancer.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 170, doi. 10.18383/j.tom.2020.00002
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Radiomic Features of Multiparametric MRI Present Stable Associations With Analogous Histological Features in Patients With Brain Cancer.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 160, doi. 10.18383/j.tom.2019.00029
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Discrimination of Malignant and Benign Breast Lesions Using Quantitative Multiparametric MRI: A Preliminary Study.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 148, doi. 10.18383/j.tom.2019.00028
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Intrasession Reliability of Arterial Spin-Labeled MRI-Measured Noncontrast Perfusion in Glioblastoma at 3 T.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 139, doi. 10.18383/j.tom.2020.00010
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Repeatability and Reproducibility of ADC Histogram Metrics from the ACRIN 6698 Breast Cancer Therapy Response Trial.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 177, doi. 10.18383/j.tom.2020.00008
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Standardization in Quantitative Imaging: A Multicenter Comparison of Radiomic Features from Different Software Packages on Digital Reference Objects and Patient Data Sets.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 118, doi. 10.18383/j.tom.2019.00031
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Stanford DRO Toolkit: Digital Reference Objects for Standardization of Radiomic Features.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 111, doi. 10.18383/j.tom.2019.00030
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Comparison of Segmentation Methods in Assessing Background Parenchymal Enhancement as a Biomarker for Response to Neoadjuvant Therapy.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 101, doi. 10.18383/j.tom.2020.00009
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The Longitudinal Imaging Tracker (BrICS-LIT): A Cloud Platform for Monitoring Treatment Response in Glioblastoma Patients.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 93, doi. 10.18383/j.tom.2020.00001
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Retrospective Correction of ADC for Gradient Nonlinearity Errors in Multicenter Breast DWI Trials: ACRIN6698 Multiplatform Feasibility Study.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 86, doi. 10.18383/j.tom.2019.00025
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Impact of MRI Protocol Adherence on Prediction of Pathological Complete Response in the I-SPY 2 Neoadjuvant Breast Cancer Trial.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 77, doi. 10.18383/j.tom.2020.00006
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Multisite Technical and Clinical Performance Evaluation of Quantitative Imaging Biomarkers from 3D FDG PET Segmentations of Head and Neck Cancer Images.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 65, doi. 10.18383/j.tom.2020.00004
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Clinical Trial Design and Development Work Group Within the Quantitative Imaging Network.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 60, doi. 10.18383/j.tom.2019.00022
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Quantitative Imaging Enters the Clinical Arena: A Personal Viewpoint.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 56, doi. 10.18383/j.tom.2020.00028
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Quantitative Imaging Network: 12 Years of Accomplishments.
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- Tomography: A Journal for Imaging Research, 2020, v. 6, n. 2, p. 55, doi. 10.18383/j.tom.2020.00504
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