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Radiotherapy Dosage

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Use of artificial neural network for pretreatment verification of intensity modulation radiation therapy fields.

The British journal of radiology Jul 24, 2019
OBJECTIVE: The accuracy of dose delivery for intensity modulated radiotherapy (IMRT) treatments should be determined by an accurate quality assurance procedure. In this work, we used artificial neural networks (ANNs) as an application for the pre-tre...
Humans Neural Networks, Computer Quality Control Radiotherapy Dosage Machine Learning Particle Accelerators Radiotherapy, Intensity-Modulated Male Nasopharyngeal Neoplasms Prostatic Neoplasms
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A preliminary study of using a deep convolution neural network to generate synthesized CT images based on CBCT for adaptive radiotherapy of nasopharyngeal carcinoma.

Physics in medicine and biology Jul 16, 2019
This study aims to utilize a deep convolutional neural network (DCNN) for synthesized CT image generation based on cone-beam CT (CBCT) and to apply the images to dose calculations for nasopharyngeal carcinoma (NPC). An encoder-decoder 2D U-Net neural...
Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Spiral Cone-Beam Computed Tomography Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy Planning, Computer-Assisted Humans Radiotherapy Dosage Neural Networks, Computer Algorithms
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MRI-based treatment planning for proton radiotherapy: dosimetric validation of a deep learning-based liver synthetic CT generation method.

Physics in medicine and biology Jul 16, 2019
Magnetic resonance imaging (MRI) has been widely used in combination with computed tomography (CT) radiation therapy because MRI improves the accuracy and reliability of target delineation due to its superior soft tissue contrast over CT. The MRI-onl...
Humans Retrospective Studies Tomography, X-Ray Computed Reproducibility of Results Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiography, Abdominal Deep Learning Liver Neoplasms Carcinoma, Hepatocellular Image Processing, Computer-Assisted
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Deep learning derived tumor infiltration maps for personalized target definition in Glioblastoma radiotherapy.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Jul 11, 2019
PURPOSE: Glioblastoma is routinely treated by concomitant radiochemotherapy. Current target definition guidelines use anatomic MRI (magnetic resonance imaging) scans, taking into account contrast enhancement and the rather unspecific hyperintensity o...
Radiotherapy Dosage Diffusion Tensor Imaging Deep Learning Glioblastoma Neoplasm Recurrence, Local Radiotherapy Planning, Computer-Assisted Brain Neoplasms Male Middle Aged Female Humans Aged Precision Medicine Aged, 80 and over Retrospective Studies Adult
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Dosimetric evaluation of synthetic CT for head and neck radiotherapy generated by a patch-based three-dimensional convolutional neural network.

Medical physics Jul 9, 2019
PURPOSE: To develop and evaluate a patch-based convolutional neural network (CNN) to generate synthetic computed tomography (sCT) images for magnetic resonance (MR)-only workflow for radiotherapy of head and neck tumors. A patch-based deep learning m...
Humans Neural Networks, Computer Radiometry Magnetic Resonance Imaging Tomography, X-Ray Computed Radiotherapy Planning, Computer-Assisted Image Processing, Computer-Assisted Radiotherapy Dosage Head and Neck Neoplasms Radiotherapy, Intensity-Modulated
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Deep Convolution Neural Network (DCNN) Multiplane Approach to Synthetic CT Generation From MR images-Application in Brain Proton Therapy.

International journal of radiation oncology, biology, physics Jul 2, 2019
PURPOSE: The first aim of this work is to present a novel deep convolution neural network (DCNN) multiplane approach and compare it to single-plane prediction of synthetic computed tomography (sCT) by using the real computed tomography (CT) as ground...
Glioblastoma Feasibility Studies Radiotherapy Planning, Computer-Assisted Head Brain Neoplasms Magnetic Resonance Imaging Multimodal Imaging Radiotherapy, Image-Guided Technology, Radiologic Radiotherapy Dosage Air Skull Proton Therapy Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Reproducibility of Results
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Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network.

Physics in medicine and biology Jun 20, 2019
An accurate prediction of achievable dose distribution on a patient specific basis would greatly improve IMRT/VMAT planning in both efficiency and quality. Recently machine learning techniques have been proposed for IMRT dose prediction based on pati...
Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiometry Humans Neural Networks, Computer Male Prostatic Neoplasms
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Three-dimensional dose prediction for lung IMRT patients with deep neural networks: robust learning from heterogeneous beam configurations.

Medical physics Jun 17, 2019
PURPOSE: The use of neural networks to directly predict three-dimensional dose distributions for automatic planning is becoming popular. However, the existing methods use only patient anatomy as input and assume consistent beam configuration for all ...
Radiation Dosage Humans Deep Learning Radiotherapy Dosage Lung Neoplasms Radiotherapy, Intensity-Modulated Radiotherapy Planning, Computer-Assisted
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Dose distribution prediction in isodose feature-preserving voxelization domain using deep convolutional neural network.

Medical physics Jun 7, 2019
PURPOSE: To implement a framework for dose prediction using a deep convolutional neural network (CNN) based on the concept of isodose feature-preserving voxelization (IFPV) in simplifying the representation of the dose distribution.
Deep Learning Radiotherapy Planning, Computer-Assisted Radiation Dosage Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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Development and Validation of a Bayesian Network Method to Detect External Beam Radiation Therapy Physician Order Errors.

International journal of radiation oncology, biology, physics May 31, 2019
PURPOSE: To investigate a Bayesian network (BN)-based method to detect errors in external beam radiation therapy physician orders.
Medical Errors Radiotherapy Setup Errors Technology, Radiologic Dose Fractionation, Radiation Radiologists Neoplasms Humans Radiotherapy, Image-Guided False Negative Reactions Radiotherapy Planning, Computer-Assisted Cohort Studies Simulation Training Neural Networks, Computer False Positive Reactions ROC Curve Datasets as Topic Algorithms Bayes Theorem Radiotherapy Dosage Organ Specificity
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