AIMC Topic: Particle Accelerators
Clear Filters Showing 1 to 10 of 39 articles
Portal dose image prediction using Monte Carlo generated transmission energy fluence maps of dynamic radiotherapy treatment plans: a deep learning approach.
Biomedical physics & engineering express
Apr 9, 2025
This work aims to develop and investigate the feasibility of a hybrid model combining Monte Carlo (MC) simulations and deep learning (DL) to predict electronic portal imaging device (EPID) images based on MC-generated exit phase space energy fluence ...
Advanced prediction of multi-leaf collimator leaf position using artificial neural network.
Medical physics
Feb 18, 2025
BACKGROUND: Multi-leaf collimators (MLCs) are crucial for modern radiotherapy as they ensure precise target irradiation through accurate leaf positioning. Accurate prediction of MLC leaf positions is vital for the effectiveness and safety of treatmen...
MR-linac: role of artificial intelligence and automation.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Jan 22, 2025
The integration of artificial intelligence (AI) into radiotherapy has advanced significantly during the past 5 years, especially in terms of automating key processes like organ at risk delineation and treatment planning. These innovations have enhanc...
Artificial intelligence for treatment delivery: image-guided radiotherapy.
Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
Aug 13, 2024
Radiation therapy (RT) is a highly digitized field relying heavily on computational methods and, as such, has a high affinity for the automation potential afforded by modern artificial intelligence (AI). This is particularly relevant where imaging is...
From plan to delivery: Machine learning based positional accuracy prediction of multi-leaf collimator and estimation of delivery effect in volumetric modulated arc therapy.
Journal of applied clinical medical physics
Jun 20, 2024
PURPOSE: The positional accuracy of MLC is an important element in establishing the exact dosimetry in VMAT. We comprehensively analyzed factors that may affect MLC positional accuracy in VMAT, and constructed a model to predict MLC positional deviat...
Assessment of the deep learning-based gamma passing rate prediction system for 1.5 T magnetic resonance-guided linear accelerator.
Radiological physics and technology
Apr 30, 2024
Measurement-based verification is impossible for the patient-specific quality assurance (QA) of online adaptive magnetic resonance imaging-guided radiotherapy (oMRgRT) because the patient remains on the couch throughout the session. We assessed a dee...
Custom-Trained Deep Learning-Based Auto-Segmentation for Male Pelvic Iterative CBCT on C-Arm Linear Accelerators.
Practical radiation oncology
Feb 6, 2024
PURPOSE: The purpose of this investigation was to evaluate the clinical applicability of a commercial artificial intelligence-driven deep learning auto-segmentation (DLAS) tool on enhanced iterative cone beam computed tomography (iCBCT) acquisitions ...
Performance assessment of variant UNet-based deep-learning dose engines for MR-Linac-based prostate IMRT plans.
Physics in medicine and biology
Aug 11, 2023
. UNet-based deep-learning (DL) architectures are promising dose engines for traditional linear accelerator (Linac) models. Current UNet-based engines, however, were designed differently with various strategies, making it challenging to fairly compar...
Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac.
Physics in medicine and biology
Nov 18, 2022
In this work we present a framework for robust deep learning-based VMAT forward dose calculations for the 1.5T MR-linac. A convolutional neural network was trained on the dose of individual multi-leaf-collimator VMAT segments and was used to predict ...
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 ...
Don't Miss the Future of Medicine
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823