AIMC Topic: Radiotherapy Dosage
Clear Filters Showing 391 to 400 of 497 articles
Knowledge-based dose prediction models for head and neck cancer are strongly affected by interorgan dependency and dataset inconsistency.
Medical physics
Dec 24, 2018
PURPOSE: The goal of this study was to generate a large treatment plan database for head and neck (H&N) cancer patients that can be considered as the gold standard to train and validate models for knowledge-based (KB) treatment planning and QA. With ...
Deep-learning based surface region selection for deep inspiration breath hold (DIBH) monitoring in left breast cancer radiotherapy.
Physics in medicine and biology
Dec 12, 2018
Deep inspiration breath hold (DIBH) with surface supervising is a common technique for cardiac dose reduction in left breast cancer radiotherapy. Surface supervision accuracy relies on the characteristics of surface region. In this study, a convoluti...
DoseNet: a volumetric dose prediction algorithm using 3D fully-convolutional neural networks.
Physics in medicine and biology
Dec 4, 2018
The goal of this study is to demonstrate the feasibility of a novel fully-convolutional volumetric dose prediction neural network (DoseNet) and test its performance on a cohort of prostate stereotactic body radiotherapy (SBRT) patients. DoseNet is su...
Automatic treatment planning based on three-dimensional dose distribution predicted from deep learning technique.
Medical physics
Nov 28, 2018
PURPOSE: To develop an automated treatment planning strategy for external beam intensity-modulated radiation therapy (IMRT), including a deep learning-based three-dimensional (3D) dose prediction and a dose distribution-based plan generation algorith...
A feasibility study on an automated method to generate patient-specific dose distributions for radiotherapy using deep learning.
Medical physics
Nov 23, 2018
PURPOSE: To develop a method for predicting optimal dose distributions, given the planning image and segmented anatomy, by applying deep learning techniques to a database of previously optimized and approved Intensity-modulated radiation therapy trea...
A study of positioning orientation effect on segmentation accuracy using convolutional neural networks for rectal cancer.
Journal of applied clinical medical physics
Nov 12, 2018
PURPOSE: Convolutional neural networks (CNN) have greatly improved medical image segmentation. A robust model requires training data can represent the entire dataset. One of the differing characteristics comes from variability in patient positioning ...
Temporal separation of Cerenkov radiation and scintillation using a clinical LINAC and artificial intelligence.
Physics in medicine and biology
Nov 9, 2018
Convolutional neural network (CNN) type artificial intelligences were trained to estimate the Cerenkov radiation present in the temporal response of a LINAC irradiated scintillator-fiber optic dosimeter. The CNN estimate of Cerenkov radiation is subt...
Auto-delineation of oropharyngeal clinical target volumes using 3D convolutional neural networks.
Physics in medicine and biology
Nov 7, 2018
Accurate clinical target volume (CTV) delineation is essential to ensure proper tumor coverage in radiation therapy. This is a particularly difficult task for head-and-neck cancer patients where detailed knowledge of the pathways of microscopic tumor...
Assessment of specific versus combined purpose knowledge based models in prostate radiotherapy.
Journal of applied clinical medical physics
Oct 19, 2018
Knowledge-based planning (KBP) can be used to improve plan quality, planning speed, and reduce the inter-patient plan variability. KPB may also identify and reduce systematic variations in VMAT plans, something very important in multi-institutional c...
Effect of machine learning methods on predicting NSCLC overall survival time based on Radiomics analysis.
Radiation oncology (London, England)
Oct 5, 2018
BACKGROUND: To investigate the effect of machine learning methods on predicting the Overall Survival (OS) for non-small cell lung cancer based on radiomics features analysis.
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