MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study
Abstract Magnetic Resonance Imaging (MRI) is increasingly being used in treatment
planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue …
planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue …
CT-based synthetic contrast-enhanced dual-energy CT generation using conditional denoising diffusion probabilistic model
Objective. The study aimed to generate synthetic contrast-enhanced Dual-energy CT (CE-
DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations …
DECT) images from non-contrast single-energy CT (SECT) scans, addressing the limitations …
CT‐based synthetic iodine map generation using conditional denoising diffusion probabilistic model
Background Iodine maps, derived from image‐processing of contrast‐enhanced dual‐
energy computed tomography (DECT) scans, highlight the differences in tissue iodine …
energy computed tomography (DECT) scans, highlight the differences in tissue iodine …
Recent advances in the clinical applications of machine learning in proton therapy
VL Wildman, JF Wynne, AH Kesarwala, X Yang - medRxiv, 2024 - medrxiv.org
The present systematic review is an effort to explore the different clinical applications and
current implementations of machine/deep learning in proton therapy. It will assist as a …
current implementations of machine/deep learning in proton therapy. It will assist as a …
A deep-learning-based surrogate model for Monte-Carlo simulations of the linear energy transfer in primary brain tumor patients treated with proton-beam …
S Starke, A Kieslich, M Palkowitsch… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. This study explores the use of neural networks (NNs) as surrogate models for
Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LET …
Monte-Carlo (MC) simulations in predicting the dose-averaged linear energy transfer (LET …
Deep learning based linear energy transfer calculation for proton therapy
X Tang, HWC Tseung, D Moseley… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. This study aims to address the limitations of traditional methods for calculating
linear energy transfer (LET), a critical component in assessing relative biological …
linear energy transfer (LET), a critical component in assessing relative biological …
Synthetic CT generation from MRI using 3D diffusion model
This study aims to simplify radiation therapy treatment planning by proposing an MRI-to-CT
transformer-based denoising diffusion probabilistic model (CT-DDPM) to generate high …
transformer-based denoising diffusion probabilistic model (CT-DDPM) to generate high …
Patient-specific 3D volumetric CBCT image reconstruction with single x-ray projection using denoising diffusion probabilistic model
This study proposes an innovative 3D diffusion-based model called the Cycle-consistency
Geometric-integrated X-ray to Computed Tomography Denoising Diffusion Probabilistic …
Geometric-integrated X-ray to Computed Tomography Denoising Diffusion Probabilistic …
Iodine map synthesis from non-contrast CT using diffusion model
Iodine maps can be obtained from contrast enhanced dual-energy compute tomography
(DECT) scans to emphasize iodine contrast agent uptake in cancer patients' tissues, which …
(DECT) scans to emphasize iodine contrast agent uptake in cancer patients' tissues, which …
Full-dose PET synthesis from low-dose PET using 2D high efficiency denoising diffusion probabilistic model
The purpose of this study is to reduce radiation exposure in PET imaging while preserving
high-quality clinical PET images. We propose the PET Consistency Model (PET-CM), an …
high-quality clinical PET images. We propose the PET Consistency Model (PET-CM), an …