AIMC Topic: Protons

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Consistency in contouring of organs at risk by artificial intelligence vs oncologists in head and neck cancer patients.

Acta oncologica (Stockholm, Sweden)
BACKGROUND: In the Danish Head and Neck Cancer Group (DAHANCA) 35 trial, patients are selected for proton treatment based on simulated reductions of Normal Tissue Complication Probability (NTCP) for proton compared to photon treatment at the referrin...

A hybrid method of correcting CBCT for proton range estimation with deep learning and deformable image registration.

Physics in medicine and biology
. This study aimed to develop a novel method for generating synthetic CT (sCT) from cone-beam CT (CBCT) of the abdomen/pelvis with bowel gas pockets to facilitate estimation of proton ranges.. CBCT, the same-day repeat CT, and the planning CT (pCT) o...

Deep learning proton beam range estimation model for quality assurance based on two-dimensional scintillated light distributions in simulations.

Medical physics
BACKGROUND: Many studies have utilized optical camera systems with volumetric scintillators for quality assurances (QA) to estimate the proton beam range. However, previous analytically driven range estimation methods have the difficulty to derive th...

Deep Learning for Inference of Hepatic Proton Density Fat Fraction From T1-Weighted In-Phase and Opposed-Phase MRI: Retrospective Analysis of Population-Based Trial Data.

AJR. American journal of roentgenology
The confounder-corrected chemical shift-encoded MRI (CSE-MRI) sequence used to determine proton density fat fraction (PDFF) for hepatic fat quantification is not widely available. As an alternative, hepatic fat can be assessed by a two-point Dixon m...

PhysVENeT: a physiologically-informed deep learning-based framework for the synthesis of 3D hyperpolarized gas MRI ventilation.

Scientific reports
Functional lung imaging modalities such as hyperpolarized gas MRI ventilation enable visualization and quantification of regional lung ventilation; however, these techniques require specialized equipment and exogenous contrast, limiting clinical adop...

A review of machine learning applications for the proton MR spectroscopy workflow.

Magnetic resonance in medicine
This literature review presents a comprehensive overview of machine learning (ML) applications in proton MR spectroscopy (MRS). As the use of ML techniques in MRS continues to grow, this review aims to provide the MRS community with a structured over...

MR-zero meets RARE MRI: Joint optimization of refocusing flip angles and neural networks to minimize T -induced blurring in spin echo sequences.

Magnetic resonance in medicine
PURPOSE: An end-to-end differentiable 2D Bloch simulation is used to reduce T induced blurring in single-shot turbo spin echo sequences, also called rapid imaging with refocused echoes (RARE) sequences, by using a joint optimization of refocusing fli...

Automated treatment planning for proton pencil beam scanning using deep learning dose prediction and dose-mimicking optimization.

Journal of applied clinical medical physics
PURPOSE: The purpose of this study is to investigate the use of a deep learning architecture for automated treatment planning for proton pencil beam scanning (PBS).

Deep learning-based protoacoustic signal denoising for proton range verification.

Biomedical physics & engineering express
Proton therapy is a type of radiation therapy that can provide better dose distribution compared to photon therapy by delivering most of the energy at the end of range, which is called the Bragg peak (BP). The protoacoustic technique was developed to...