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Radiotherapy Dosage

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An ultra-fast deep-learning-based dose engine for prostate VMAT via knowledge distillation framework with limited patient data.

Physics in medicine and biology
. Deep-learning (DL)-based dose engines have been developed to alleviate the intrinsic compromise between the calculation accuracy and efficiency of the traditional dose calculation algorithms. However, current DL-based engines typically possess high...

SWFT-Net: a deep learning framework for efficient fine-tuning spot weights towards adaptive proton therapy.

Physics in medicine and biology
. One critical task for adaptive proton therapy is how to perform spot weight re-tuning and reoptimize plan, both of which are time-consuming and labor intensive. We proposed a deep learning framework (SWFT-Net) to speed up such a task, a starting po...

Deep learning architecture with transformer and semantic field alignment for voxel-level dose prediction on brain tumors.

Medical physics
PURPOSE: The use of convolution neural networks (CNN) to accurately predict dose distributions can accelerate intensity-modulated radiation therapy (IMRT) planning. The purpose of our study is to develop a novel deep learning architecture for precise...

Tissues margin-based analytical anisotropic algorithm boosting method via deep learning attention mechanism with cervical cancer.

International journal of computer assisted radiology and surgery
PURPOSE: Speed and accuracy are two critical factors in dose calculation for radiotherapy. Analytical Anisotropic Algorithm (AAA) is a rapid dose calculation algorithm but has dose errors in tissue margin area. Acuros XB (AXB) has high accuracy but t...

X-ray dose profiles using artificial neural networks.

Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine
This paper introduces a novel computational method to simulate and predict radiation dose profiles in a water phantom irradiated by X-rays of 6 and 15 MV at different depths and field sizes using Artificial Neural Networks within the error margin req...

Deep Learning-based Non-rigid Image Registration for High-dose Rate Brachytherapy in Inter-fraction Cervical Cancer.

Journal of digital imaging
In this study, an inter-fraction organ deformation simulation framework for the locally advanced cervical cancer (LACC), which considers the anatomical flexibility, rigidity, and motion within an image deformation, was proposed. Data included 57 CT s...

Robust deep learning-based forward dose calculations for VMAT on the 1.5T MR-linac.

Physics in medicine and biology
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 ...

Input feature design and its impact on the performance of deep learning models for predicting fluence maps in intensity-modulated radiation therapy.

Physics in medicine and biology
. Deep learning (DL) models for fluence map prediction (FMP) have great potential to reduce treatment planning time in intensity-modulated radiation therapy (IMRT) by avoiding the lengthy inverse optimization process. This study aims to improve the r...

A high-performance method of deep learning for prostate MR-only radiotherapy planning using an optimized Pix2Pix architecture.

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)
PURPOSE: The first aim was to generate and compare synthetic-CT (sCT) images using a conditional generative adversarial network (cGAN) method (Pix2Pix) for MRI-only prostate radiotherapy planning by testing several generators, loss functions, and hyp...

Efficient dose-volume histogram-based pretreatment patient-specific quality assurance methodology with combined deep learning and machine learning models for volumetric modulated arc radiotherapy.

Medical physics
BACKGROUND: Weak correlation between gamma passing rates and dose differences in target volumes and organs at risk (OARs) has been reported in several studies. Evaluation on the differences between planned dose-volume histogram (DVH) and reconstructe...