AI Medical Compendium Journal:
International journal of radiation oncology, biology, physics

Showing 51 to 60 of 93 articles

Dosimetry-Driven Quality Measure of Brain Pseudo Computed Tomography Generated From Deep Learning for MRI-Only Radiation Therapy Treatment Planning.

International journal of radiation oncology, biology, physics May 14, 2020
PURPOSE: This study aims to evaluate the impact of key parameters on the pseudo computed tomography (pCT) quality generated from magnetic resonance imaging (MRI) with a 3-dimensional (3D) convolutional neural network.
Contrast Media Humans Brain Neural Networks, Computer Magnetic Resonance Imaging Retrospective Studies Radiotherapy Tomography, X-Ray Computed Skull Brain Neoplasms Radiometry Deep Learning
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RapidBrachyDL: Rapid Radiation Dose Calculations in Brachytherapy Via Deep Learning.

International journal of radiation oncology, biology, physics May 12, 2020
PURPOSE: Detailed and accurate absorbed dose calculations from radiation interactions with the human body can be obtained with the Monte Carlo (MC) method. However, the MC method can be slow for use in the time-sensitive clinical workflow. The aim of...
Monte Carlo Method Urinary Bladder Iridium Radioisotopes Organs at Risk Radiotherapy Planning, Computer-Assisted Brachytherapy Radiotherapy Dosage Retrospective Studies Humans Neural Networks, Computer Female Deep Learning Uterine Cervical Neoplasms Prostatic Neoplasms Male Prostate Rectum Colon, Sigmoid
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Knowledge-Based Tradeoff Hyperplanes for Head and Neck Treatment Planning.

International journal of radiation oncology, biology, physics Jan 24, 2020
PURPOSE: To develop a tradeoff hyperplane model to facilitate tradeoff decision-making before inverse planning.
Humans Head and Neck Neoplasms Knowledge Bases Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Radiotherapy, Intensity-Modulated
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Quantitative Thermal Imaging Biomarkers to Detect Acute Skin Toxicity From Breast Radiation Therapy Using Supervised Machine Learning.

International journal of radiation oncology, biology, physics Jan 23, 2020
PURPOSE: Radiation-induced dermatitis is a common side effect of breast radiation therapy (RT). Current methods to evaluate breast skin toxicity include clinical examination, visual inspection, and patient-reported symptoms. Physiological changes ass...
Biomarkers Female Aged Aged, 80 and over Adult Humans Molecular Imaging Skin Temperature Radiodermatitis Breast Neoplasms Middle Aged Skin Supervised Machine Learning
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Comparison of Deep Learning-Based and Patch-Based Methods for Pseudo-CT Generation in MRI-Based Prostate Dose Planning.

International journal of radiation oncology, biology, physics Sep 7, 2019
PURPOSE: Deep learning methods (DLMs) have recently been proposed to generate pseudo-CT (pCT) for magnetic resonance imaging (MRI) based dose planning. This study aims to evaluate and compare DLMs (U-Net and generative adversarial network [GAN]) usin...
Bone and Bones Urinary Bladder Uncertainty Femur Head Reference Values Radiotherapy Dosage Radiotherapy, Intensity-Modulated Humans Tomography, X-Ray Computed Male Deep Learning Magnetic Resonance Imaging Prostatic Neoplasms Prostate Pelvis Rectum
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Machine Learning for Patient-Specific Quality Assurance of VMAT: Prediction and Classification Accuracy.

International journal of radiation oncology, biology, physics Aug 1, 2019
PURPOSE: To assess the accuracy of machine learning to predict and classify quality assurance (QA) results for volumetric modulated arc therapy (VMAT) plans.
Radiotherapy Planning, Computer-Assisted Data Accuracy Quality Assurance, Health Care Genital Neoplasms, Female Radiotherapy, Intensity-Modulated Head and Neck Neoplasms Poisson Distribution Regression Analysis Workload Humans Machine Learning Female Reproducibility of Results Sensitivity and Specificity
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Radiomics Analysis for Glioma Malignancy Evaluation Using Diffusion Kurtosis and Tensor Imaging.

International journal of radiation oncology, biology, physics Jul 22, 2019
PURPOSE: A noninvasive diagnostic method to predict the degree of malignancy accurately would be of great help in glioma management. This study aimed to create a highly accurate machine learning model to perform glioma grading.
Diffusion Tensor Imaging Anisotropy Diffusion Magnetic Resonance Imaging Astrocytoma Oligodendroglioma Female Aged Aged, 80 and over Young Adult Adult Humans Machine Learning Brain Neoplasms Retrospective Studies Glioma Male Diagnosis, Differential Middle Aged Glioblastoma Adolescent Neoplasm Grading Datasets as Topic
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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...
Humans Neural Networks, Computer Algorithms Tomography, X-Ray Computed Air Glioblastoma Reproducibility of Results Skull Brain Neoplasms Feasibility Studies Proton Therapy Magnetic Resonance Imaging Radiotherapy Planning, Computer-Assisted Radiotherapy, Image-Guided Multimodal Imaging Head Technology, Radiologic Radiotherapy Dosage
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A Deep Learning Model for Predicting Xerostomia Due to Radiation Therapy for Head and Neck Squamous Cell Carcinoma in the RTOG 0522 Clinical Trial.

International journal of radiation oncology, biology, physics Jun 13, 2019
PURPOSE: Xerostomia commonly occurs in patients who undergo head and neck radiation therapy and can seriously affect patients' quality of life. In this study, we developed a xerostomia prediction model with radiation treatment data using a 3-dimensio...
Radiotherapy Planning, Computer-Assisted ROC Curve Pharyngeal Neoplasms Radiotherapy, Conformal Logistic Models Humans Radiotherapy, Image-Guided Oropharyngeal Neoplasms Squamous Cell Carcinoma of Head and Neck Laryngeal Neoplasms Retrospective Studies Submandibular Gland Area Under Curve Tomography, X-Ray Computed Xerostomia Parotid Gland Deep Learning Hypopharyngeal Neoplasms
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Markerless Pancreatic Tumor Target Localization Enabled By Deep Learning.

International journal of radiation oncology, biology, physics Jun 13, 2019
PURPOSE: Deep learning is an emerging technique that allows us to capture imaging information beyond the visually recognizable level of a human being. Because of the anatomic characteristics and location, on-board target verification for radiation de...
Pancreatic Neoplasms Radiography Datasets as Topic Pancreas Radiotherapy, Image-Guided Humans Fiducial Markers Neural Networks, Computer Organ Motion Deep Learning Image Processing, Computer-Assisted
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