AIMC Topic: Proton Therapy

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Convolutional neural network based proton stopping-power-ratio estimation with dual-energy CT: a feasibility study.

Physics in medicine and biology Nov 3, 2020
Dual-energy computed tomography (DECT) has shown a great potential for lowering range uncertainties, which is necessary for truly leveraging the Bragg peak in proton therapy. However, analytical stopping-power-ratio (SPR) estimation methods have limi...
Neural Networks, Computer Tomography, X-Ray Computed Male Image Processing, Computer-Assisted Humans Phantoms, Imaging Proton Therapy Uncertainty Protons Prostatic Neoplasms Feasibility Studies Calibration Signal-To-Noise Ratio
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Fast spot-scanning proton dose calculation method with uncertainty quantification using a three-dimensional convolutional neural network.

Physics in medicine and biology Oct 26, 2020
This study proposes a near-real-time spot-scanning proton dose calculation method with probabilistic uncertainty estimation using a three-dimensional convolutional neural network (3D-CNN). CT images and clinical target volume contours of 215 head and...
Proton Therapy Uncertainty Humans Neural Networks, Computer Tomography, X-Ray Computed Head and Neck Neoplasms
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Deep learning-enabled MRI-only photon and proton therapy treatment planning for paediatric abdominal tumours.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Oct 7, 2020
PURPOSE: To assess the feasibility of magnetic resonance imaging (MRI)-only treatment planning for photon and proton radiotherapy in children with abdominal tumours.
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Abdominal Neoplasms Proton Therapy Deep Learning Humans Child, Preschool Child Magnetic Resonance Imaging
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A machine learning framework with anatomical prior for online dose verification using positron emitters and PET in proton therapy.

Physics in medicine and biology Sep 14, 2020
We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information o...
Humans Positron-Emission Tomography Radiation Dosage Signal-To-Noise Ratio Radiotherapy Dosage Neural Networks, Computer Machine Learning Image Processing, Computer-Assisted Electrons Proton Therapy Uncertainty
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Prediction of the output factor using machine and deep learning approach in uniform scanning proton therapy.

Journal of applied clinical medical physics May 17, 2020
PURPOSE: The purpose of this work is to develop machine and deep learning-based models to predict output and MU based on measured patient quality assurance (QA) data in uniform scanning proton therapy (USPT).
Deep Learning Normal Distribution Proton Therapy Humans Neural Networks, Computer Algorithms
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Comparison of CBCT based synthetic CT methods suitable for proton dose calculations in adaptive proton therapy.

Physics in medicine and biology Apr 28, 2020
In-room imaging is a prerequisite for adaptive proton therapy. The use of onboard cone-beam computed tomography (CBCT) imaging, which is routinely acquired for patient position verification, can enable daily dose reconstructions and plan adaptation d...
Cone-Beam Computed Tomography Image Processing, Computer-Assisted Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Proton Therapy Radiometry Aged, 80 and over Adult Male Middle Aged Neural Networks, Computer Female Aged Humans
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High quality proton portal imaging using deep learning for proton radiation therapy: a phantom study.

Biomedical physics & engineering express Apr 27, 2020
Purpose; For shoot-through proton treatments, like FLASH radiotherapy, there will be protons exiting the patient which can be used for proton portal imaging (PPI), revealing valuable information for the validation of tumor location in the beam's-eye-...
Humans Phantoms, Imaging Reproducibility of Results Nonlinear Dynamics Neural Networks, Computer Proton Therapy Neoplasms Protons Signal-To-Noise Ratio Deep Learning Algorithms Radiotherapy Image Processing, Computer-Assisted Computer Simulation Scattering, Radiation
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Patient selection for proton therapy: a radiobiological fuzzy Markov model incorporating robust plan analysis.

Physical and engineering sciences in medicine Feb 10, 2020
While proton therapy can offer increased sparing of healthy tissue compared with X-ray therapy, it can be difficult to predict whether a benefit can be expected for an individual patient. Predictive modelling may aid in this respect. However, the pre...
Markov Chains Quality-Adjusted Life Years Radiotherapy, Intensity-Modulated Life Expectancy Proton Therapy Humans Uncertainty Models, Theoretical Fuzzy Logic Patient Selection Probability Female Quality of Life Child, Preschool
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A deep learning approach for converting prompt gamma images to proton dose distributions: A Monte Carlo simulation study.

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) Dec 20, 2019
PURPOSE: In proton therapy, imaging prompt gamma (PG) rays has the potential to verify proton dose (PD) distribution. Despite the fact that there is a strong correlation between the gamma-ray emission and PD, they are still different in terms of the ...
Brain Computer Simulation Tomography, X-Ray Computed Reproducibility of Results Humans Neural Networks, Computer Algorithms Proton Therapy Gamma Rays Protons Deep Learning Image Processing, Computer-Assisted Monte Carlo Method Phantoms, Imaging
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A dual-stream deep convolutional network for reducing metal streak artifacts in CT images.

Physics in medicine and biology Nov 26, 2019
Machine learning and deep learning are rapidly finding applications in the medical imaging field. In this paper, we address the long-standing problem of metal artifacts in computed tomography (CT) images by training a dual-stream deep convolutional n...
Metals Algorithms Image Processing, Computer-Assisted Humans Tomography, X-Ray Computed Artifacts Neural Networks, Computer Prostheses and Implants Reproducibility of Results Pedicle Screws Machine Learning Deep Learning Proton Therapy Visible Human Projects
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