AIMC Topic: Radiotherapy, Intensity-Modulated
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DR-only Carbon-ion radiotherapy treatment planning via deep learning.
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)
Jul 4, 2022
PURPOSE: To evaluate the feasibility of patient-specific digital radiography (DR)-only treatment planning for carbon ion radiotherapy in anthropomorphic thorax-and-abdomen phantom and head-and-neck patients.
Machine learning models to predict the delivered positions of Elekta multileaf collimator leaves for volumetric modulated arc therapy.
Journal of applied clinical medical physics
Jun 7, 2022
PURPOSE: Accurate positioning of multileaf collimator (MLC) leaves during volumetric modulated arc therapy (VMAT) is essential for accurate treatment delivery. We developed a linear regression, support vector machine, random forest, extreme gradient ...
Treatment plan prediction for lung IMRT using deep learning based fluence map generation.
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)
May 21, 2022
PURPOSE: Recently, it has been shown that automated treatment planning can be executed by direct fluence prediction from patient anatomy using convolutional neural networks. Proof of principle publications utilise a fixed dose prescription and fixed ...
Toward automatic beam angle selection for pencil-beam scanning proton liver treatments: A deep learning-based approach.
Medical physics
May 11, 2022
BACKGROUND: Dose deposition characteristics of proton radiation can be advantageous over photons. Proton treatment planning, however, poses additional challenges for the planners. Proton therapy is usually delivered with only a small number of beam a...
Dose prediction via distance-guided deep learning: Initial development for nasopharyngeal carcinoma radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 26, 2022
BACKGROUND AND PURPOSE: Geometric information such as distance information is essential for dose calculations in radiotherapy. However, state-of-the-art dose prediction methods use only binary masks without distance information. This study aims to de...
The feasibility study on the generalization of deep learning dose prediction model for volumetric modulated arc therapy of cervical cancer.
Journal of applied clinical medical physics
Mar 9, 2022
PURPOSE: To develop a 3D-Unet dose prediction model to predict the three-dimensional dose distribution of volumetric modulated arc therapy (VMAT) for cervical cancer and test the dose prediction performance of the model in endometrial cancer to explo...
Accelerate treatment planning process using deep learning generated fluence maps for cervical cancer radiation therapy.
Medical physics
Feb 25, 2022
PURPOSE: This study aims to develop a deep learning method that skips the time-consuming inverse optimization process for automatic generation of machine-deliverable intensity-modulated radiation therapy (IMRT) plans.
Deep learning driven predictive treatment planning for adaptive radiotherapy of lung cancer.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Feb 18, 2022
BACKGROUND AND PURPOSE: To develop a novel deep learning algorithm of sequential analysis, Seq2Seq, for predicting weekly anatomical changes of lung tumor and esophagus during definitive radiotherapy, incorporate the potential tumor shrinkage into a ...
A feasibility study for in vivo treatment verification of IMRT using Monte Carlo dose calculation and deep learning-based modelling of EPID detector response.
Radiation oncology (London, England)
Feb 10, 2022
BACKGROUND: This paper describes the development of a predicted electronic portal imaging device (EPID) transmission image (TI) using Monte Carlo (MC) and deep learning (DL). The measured and predicted TI were compared for two-dimensional in vivo rad...
A hybrid optimization strategy for deliverable intensity-modulated radiotherapy plan generation using deep learning-based dose prediction.
Medical physics
Feb 9, 2022
PURPOSE: To propose a clinically feasible automatic planning solution for external beam intensity-modulated radiotherapy, including dose prediction via a deep learning and voxel-based optimization strategy.
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