AIMC Topic: Proton Therapy

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Learning-based synthetic dual energy CT imaging from single energy CT for stopping power ratio calculation in proton radiation therapy.

The British journal of radiology Oct 28, 2021
OBJECTIVE: Dual energy CT (DECT) has been shown to estimate stopping power ratio (SPR) map with a higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. This work presents a learning-based...
Humans Carcinoma, Squamous Cell Head and Neck Neoplasms Radiotherapy Planning, Computer-Assisted Proton Therapy Machine Learning Retrospective Studies Tomography, X-Ray Computed
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Calibrated uncertainty estimation for interpretable proton computed tomography image correction using Bayesian deep learning.

Physics in medicine and biology Mar 16, 2021
Integrated-type proton computed tomography (pCT) measures proton stopping power ratio (SPR) images for proton therapy treatment planning, but its image quality is degraded due to noise and scatter. Although several correction methods have been propos...
Uncertainty Protons Monte Carlo Method Phantoms, Imaging Reproducibility of Results Neural Networks, Computer Proton Therapy Deep Learning Algorithms Image Processing, Computer-Assisted Tomography, X-Ray Computed Humans Head Head and Neck Neoplasms Calibration Bayes Theorem
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Comparison of the suitability of CBCT- and MR-based synthetic CTs for daily adaptive proton therapy in head and neck patients.

Physics in medicine and biology Dec 5, 2020
Cone-beam computed tomography (CBCT)- and magnetic resonance (MR)-images allow a daily observation of patient anatomy but are not directly suited for accurate proton dose calculations. This can be overcome by creating synthetic CTs (sCT) using deep c...
Aged Adult Male Humans Neural Networks, Computer Female Head and Neck Neoplasms Magnetic Resonance Imaging Organs at Risk Radiotherapy Planning, Computer-Assisted Middle Aged Cone-Beam Computed Tomography Image Processing, Computer-Assisted Radiotherapy Dosage Proton Therapy
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Deep learning prediction of proton and photon dose distributions for paediatric abdominal tumours.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Nov 29, 2020
OBJECTIVE: Dose prediction using deep learning networks prior to radiotherapy might lead tomore efficient modality selections. The study goal was to predict proton and photon dose distributions based on the patient-specific anatomy and to assess thei...
Humans Deep Learning Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Protons Radiotherapy, Intensity-Modulated Child Organs at Risk Abdominal Neoplasms Proton Therapy
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Feasibility study of range verification based on proton-induced acoustic signals and recurrent neural network.

Physics in medicine and biology Nov 5, 2020
Range verification in proton therapy is a critical quality assurance task. We studied the feasibility of online range verification based on proton-induced acoustic signals, using a bidirectional long-short-term-memory recurrent neural network and var...
Signal Processing, Computer-Assisted Feasibility Studies Acoustics Phantoms, Imaging Proton Therapy Radiotherapy Dosage Monte Carlo Method Humans Neural Networks, Computer
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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...
Protons Phantoms, Imaging Tomography, X-Ray Computed Proton Therapy Male Humans Uncertainty Image Processing, Computer-Assisted Neural Networks, Computer Calibration Signal-To-Noise Ratio Prostatic Neoplasms Feasibility Studies
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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...
Uncertainty Tomography, X-Ray Computed Head and Neck Neoplasms Proton Therapy Humans Neural Networks, Computer
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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.
Proton Therapy Humans Magnetic Resonance Imaging Radiotherapy Dosage Deep Learning Radiotherapy Planning, Computer-Assisted Abdominal Neoplasms Child, Preschool Child
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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...
Proton Therapy Humans Uncertainty Neural Networks, Computer Image Processing, Computer-Assisted Radiation Dosage Machine Learning Electrons Signal-To-Noise Ratio Positron-Emission Tomography Radiotherapy Dosage
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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).
Humans Deep Learning Neural Networks, Computer Normal Distribution Algorithms Proton Therapy
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