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Deep learning‐based virtual noncontrast CT for volumetric modulated arc therapy planning: Comparison with a dual‐energy CT‐based approach
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/hed.23532openalex-snapshot
Long‐term experience with reduced planning target volume margins and intensity‐modulated radiotherapy with daily image‐guidance for head and neck cancer
inferredcites →https://doi.org/10.1002/mp.12045openalex-snapshot
Segmentation of organs‐at‐risks in head and neck CT images using convolutional neural networks
inferredcites →https://doi.org/10.1002/mp.12155openalex-snapshot
MR-based synthetic CT generation using a deep convolutional neural network method
inferredcites →https://doi.org/10.1002/mp.13180openalex-snapshot
Treatment planning based on water density image generated using dual‐energy computed tomography for pancreatic cancer with contrast‐enhancing agent: Phantom and clinical study
inferredcites →https://doi.org/10.1002/mp.13264openalex-snapshot
Deep learning in medical imaging and radiation therapy
inferredcites →https://doi.org/10.1002/mp.13271openalex-snapshot
Automatic treatment planning based on three‐dimensional dose distribution predicted from deep learning technique
inferredcites →https://doi.org/10.1002/mp.13490openalex-snapshot
A deep learning method for prediction of three‐dimensional dose distribution of helical tomotherapy
inferredcites →https://doi.org/10.1007/s00066-009-1927-6openalex-snapshot
Influence of Intravenous Contrast Agent on Dose Calculation in 3-D Treatment Planning for Radiosurgery of Cerebral Arteriovenous Malformations
inferredcites →https://doi.org/10.1007/s00261-016-1035-xopenalex-snapshot
“How to” incorporate dual-energy imaging into a high volume abdominal imaging practice
inferredcites →https://doi.org/10.1016/j.acra.2013.01.010openalex-snapshot
Tin-filter Enhanced Dual-Energy-CT
inferredcites →https://doi.org/10.1016/j.acra.2016.09.002openalex-snapshot
Variability of CT Attenuation Measurements in Virtual Unenhanced Images Generated Using Multimaterial Decomposition from Fast Kilovoltage-switching Dual-energy CT
inferredcites →https://doi.org/10.1016/j.ejmp.2014.09.003openalex-snapshot
Volumetric-modulated arc therapy for oropharyngeal carcinoma: A dosimetric and delivery efficiency comparison with static-field IMRT
inferredcites →https://doi.org/10.1016/j.ejmp.2019.03.022openalex-snapshot
Volumetric modulated arc therapy planning based on virtual monochromatic images: Effect of inaccurate CT numbers on dose distributions
inferredcites →https://doi.org/10.1016/j.ejrad.2011.01.087openalex-snapshot
Iodine removal in intravenous dual-energy CT-cholangiography: Is virtual non-enhanced imaging effective to replace true non-enhanced imaging?
inferredcites →https://doi.org/10.1016/j.ejrad.2011.03.042openalex-snapshot
Virtual unenhanced second generation dual-source CT of the liver: Is it time to discard the conventional unenhanced phase?
inferredcites →https://doi.org/10.1016/j.ejrad.2014.06.017openalex-snapshot
Incidental adrenal lesions detected on enhanced abdominal dual-energy CT: Can the diagnostic workup be shortened by the implementation of virtual unenhanced images?
inferredcites →https://doi.org/10.1016/j.ijrobp.2009.03.033openalex-snapshot
Volumetric Modulated Arc Therapy: Planning and Evaluation for Prostate Cancer Cases
inferredcites →https://doi.org/10.1016/j.ijrobp.2009.06.031openalex-snapshot
Results of a Multi-Institution Deformable Registration Accuracy Study (MIDRAS)
inferredcites →https://doi.org/10.1016/j.ijrobp.2011.09.015openalex-snapshot
A Comprehensive Comparison of IMRT and VMAT Plan Quality for Prostate Cancer Treatment
inferredcites →https://doi.org/10.1016/j.radonc.2007.05.015openalex-snapshot
Influence of contrast materials on dose calculation in radiotherapy planning using computed tomography for tumors at various anatomical regions: A prospective study
inferredcites →https://doi.org/10.1016/j.radonc.2017.10.032openalex-snapshot
International guideline for the delineation of the clinical target volumes (CTV) for nasopharyngeal carcinoma
inferredcites →https://doi.org/10.1016/j.radonc.2018.01.012openalex-snapshot
Clinical implementation of contrast-enhanced four-dimensional dual-energy computed tomography for target delineation of pancreatic cancer
inferredcites →https://doi.org/10.1016/j.radonc.2018.06.032openalex-snapshot
The impact of margin reduction on outcome and toxicity in head and neck cancer patients treated with image-guided volumetric modulated arc therapy (VMAT)
inferredcites →https://doi.org/10.1088/1361-6560/ab1e9dopenalex-snapshot
Influence of intravenous contrast agent on dose calculation in proton therapy using dual energy CT
inferredcites →https://doi.org/10.1093/jrr/rrz030openalex-snapshot
Deep convolutional neural network for reduction of contrast-enhanced region on CT images
inferredcites →https://doi.org/10.1109/isbi.2018.8363679openalex-snapshot
Brain MRI super resolution using 3D deep densely connected neural networks
inferredcites →https://doi.org/10.1109/tip.2003.819861openalex-snapshot
Image quality assessment: from error visibility to structural similarity
inferredcites →https://doi.org/10.1109/tmi.2013.2281719openalex-snapshot
A Flexible Method for Multi-Material Decomposition of Dual-Energy CT Images
inferredcites →https://doi.org/10.1118/1.3673772openalex-snapshot
A method to estimate the effect of deformable image registration uncertainties on daily dose mapping
inferredcites →https://doi.org/10.1148/radiol.11100978openalex-snapshot
Virtual Monochromatic Spectral Imaging with Fast Kilovoltage Switching: Improved Image Quality as Compared with That Obtained with Conventional 120-kVp CT
inferredcites →https://doi.org/10.1148/radiol.14131480openalex-snapshot
State of the Art: Dual-Energy CT of the Abdomen
inferredcites →https://doi.org/10.1148/radiol.2019181100openalex-snapshot
Virtual Unenhanced Images at Dual-Energy CT: Influence on Renal Lesion Characterization
inferredcites →https://doi.org/10.1186/1748-717x-9-168openalex-snapshot
Radiotherapy treatment planning with contrast-enhanced computed tomography: feasibility of dual-energy virtual unenhanced imaging for improved dose calculations
inferredcites →https://doi.org/10.1364/boe.8.000679openalex-snapshot
aLow-dose CT via convolutional neural network
inferredcites →https://doi.org/10.2214/ajr.17.18248openalex-snapshot
Abdominal Attenuation Values on Virtual and True Unenhanced Images Obtained With Third-Generation Dual-Source Dual-Energy CT
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.2139/ssrn.4567894openalex-extracted
Virtual Unenhanced Dual-Energy CT for Photon Radiotherapy: The Effect on Dose Distribution and CBCT Based Position Verification
inferred← citeshttps://doi.org/10.1002/mp.14319openalex-snapshot
Noise and spatial resolution properties of a commercially available deep learning‐based CT reconstruction algorithm
inferred← citeshttps://doi.org/10.1002/mp.15310openalex-snapshot
A conventional‐to‐spectral CT image translation augmentation workflow for robust contrast injection‐independent organ segmentation
inferred← citeshttps://doi.org/10.1007/s11548-023-02862-wopenalex-snapshot
Applications of deep learning to reduce the need for iodinated contrast media for CT imaging: a systematic review
inferred← citeshttps://doi.org/10.1007/s12194-024-00802-0openalex-snapshot
Variation in Hounsfield unit calculated using dual-energy computed tomography: comparison of dual-layer, dual-source, and fast kilovoltage switching technique
inferred← citeshttps://doi.org/10.1016/j.meddos.2021.03.006openalex-snapshot
Dual-energy computed tomography image-based volumetric-modulated arc therapy planning for reducing the effect of contrast-enhanced agent on dose distributions
inferred← citeshttps://doi.org/10.1016/j.phro.2024.100545openalex-snapshot
Virtual unenhanced dual-energy computed tomography for photon radiotherapy: The effect on dose distribution and cone-beam computed tomography based position verification
inferred← citeshttps://doi.org/10.1088/1361-6560/ac0758openalex-snapshot
Contrast-enhanced to noncontrast CT transformation via an adjacency content-transfer-based deep subtraction residual neural network
inferred← citeshttps://doi.org/10.3389/fonc.2026.1764560openalex-snapshot
Generation of deep learning based virtual contrast-enhanced CT images from noncontrast CT images for target volume delineation in cervical cancer radiotherapy
inferred← citeshttps://doi.org/10.3390/diagnostics12061489openalex-snapshot
A Survey on Deep Learning for Precision Oncology
inferred← citeshttps://doi.org/10.70675/a41cd36fz1d22z4a94z96fcz5fa1cbe7c6c4openalex-snapshot
Automated biomarkers extraction on conventional computed tomagraphy scanners
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