AIMC Topic: Radiotherapy, Intensity-Modulated

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Implementation of deep learning-based auto-segmentation for radiotherapy planning structures: a workflow study at two cancer centers.

Radiation oncology (London, England) Jun 8, 2021
PURPOSE: We recently described the validation of deep learning-based auto-segmented contour (DC) models for organs at risk (OAR) and clinical target volumes (CTV). In this study, we evaluate the performance of implemented DC models in the clinical ra...
Image Processing, Computer-Assisted Head and Neck Neoplasms Prostatic Neoplasms Tomography, X-Ray Computed Male Deep Learning Health Plan Implementation Radiotherapy Dosage Radiotherapy, Intensity-Modulated Central Nervous System Neoplasms Workflow Organs at Risk Radiotherapy Planning, Computer-Assisted Humans Algorithms Prognosis
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DVHnet: A deep learning-based prediction of patient-specific dose volume histograms for radiotherapy planning.

Medical physics Apr 18, 2021
PURPOSE: To develop a deep learning method to predict patient-specific dose volume histograms (DVHs) for radiotherapy planning.
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Nasopharyngeal Neoplasms Deep Learning Organs at Risk Radiotherapy Planning, Computer-Assisted Humans
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Evaluation of a highly refined prediction model in knowledge-based volumetric modulated arc therapy planning for cervical cancer.

Radiation oncology (London, England) Mar 22, 2021
BACKGROUND AND PURPOSE: To explore whether a highly refined dose volume histograms (DVH) prediction model can improve the accuracy and reliability of knowledge-based volumetric modulated arc therapy (VMAT) planning for cervical cancer.
Organs at Risk Radiotherapy Planning, Computer-Assisted Radiotherapy, Intensity-Modulated Uterine Cervical Neoplasms Knowledge Bases Humans Female
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Radiation therapy dose prediction for left-sided breast cancers using two-dimensional and three-dimensional deep learning models.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 20, 2021
PURPOSE: To develop a deep learning model capable of producing clinically acceptable dose distributions for left-sided breast cancers for 3D-CRT while exploring the use of two-dimensional versus three-dimensional anatomical data.
Radiotherapy Dosage Radiotherapy, Intensity-Modulated Unilateral Breast Neoplasms Breast Neoplasms Deep Learning Radiotherapy Planning, Computer-Assisted Humans Female
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Deep learning dose prediction for IMRT of esophageal cancer: The effect of data quality and quantity on model performance.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Mar 10, 2021
PURPOSE: To investigate the effect of data quality and quantity on the performance of deep learning (DL) models, for dose prediction of intensity-modulated radiotherapy (IMRT) of esophageal cancer.
Esophageal Neoplasms Organs at Risk Radiotherapy Planning, Computer-Assisted Data Accuracy Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans Retrospective Studies Deep Learning
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DeepDose: a robust deep learning-based dose engine for abdominal tumours in a 1.5 T MRI radiotherapy system.

Physics in medicine and biology Mar 9, 2021
We present a robust deep learning-based framework for dose calculations of abdominal tumours in a 1.5 T MRI radiotherapy system. For a set of patient plans, a convolutional neural network is trained on the dose of individual multi-leaf-collimator seg...
Male Deep Learning Magnetic Resonance Imaging Humans Neural Networks, Computer Reproducibility of Results Neoplasm Metastasis Radiotherapy Dosage Radiotherapy, Intensity-Modulated Monte Carlo Method Prostatic Neoplasms Rectal Neoplasms Radiotherapy Planning, Computer-Assisted Abdominal Neoplasms Particle Accelerators
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Clinical feasibility of deep learning-based auto-segmentation of target volumes and organs-at-risk in breast cancer patients after breast-conserving surgery.

Radiation oncology (London, England) Feb 25, 2021
BACKGROUND: In breast cancer patients receiving radiotherapy (RT), accurate target delineation and reduction of radiation doses to the nearby normal organs is important. However, manual clinical target volume (CTV) and organs-at-risk (OARs) segmentat...
Radiometry Mastectomy, Segmental Radiotherapy Planning, Computer-Assisted Observer Variation Radiotherapy, Intensity-Modulated Tomography, X-Ray Computed Female Aged Humans Deep Learning Feasibility Studies Organs at Risk Adult Breast Neoplasms Middle Aged
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Deep learning-augmented radiotherapy visualization with a cylindrical radioluminescence system.

Physics in medicine and biology Feb 9, 2021
This study aims to demonstrate a low-cost camera-based radioluminescence imaging system (CRIS) for high-quality beam visualization that encourages accurate pre-treatment verifications on radiation delivery in external beam radiotherapy. To ameliorate...
Deep Learning Image Processing, Computer-Assisted Luminescence Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans Radiometry
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Systematic method for a deep learning-based prediction model for gamma evaluation in patient-specific quality assurance of volumetric modulated arc therapy.

Medical physics Jan 28, 2021
PURPOSE: This study aimed to develop and evaluate a novel strategy for establishing a deep learning-based gamma passing rate (GPR) prediction model for volumetric modulated arc therapy (VMAT) using dummy target plan data, one measurement process, and...
Radiotherapy, Intensity-Modulated Gamma Rays Humans Neural Networks, Computer Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage
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Detecting MLC modeling errors using radiomics-based machine learning in patient-specific QA with an EPID for intensity-modulated radiation therapy.

Medical physics Jan 27, 2021
PURPOSE: We sought to develop machine learning models to detect multileaf collimator (MLC) modeling errors with the use of radiomic features of fluence maps measured in patient-specific quality assurance (QA) for intensity-modulated radiation therapy...
Gamma Rays Radiotherapy Dosage Radiotherapy, Intensity-Modulated Radiometry Humans Machine Learning Radiotherapy Planning, Computer-Assisted
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