AIMC Topic: Radiation Dosage
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Dose calculation in nuclear medicine with magnetic resonance imaging images using Monte Carlo method.
Radiation protection dosimetry
May 27, 2025
In recent years, scientists have been trying to convert magnetic resonance imaging (MRI) images into computed tomography (CT) images for dose calculations while taking advantage of the benefits of MRI images. The main approaches for image conversion ...
Improvement of deep learning-based dose conversion accuracy to a Monte Carlo algorithm in proton beam therapy for head and neck cancers.
Journal of radiation research
May 23, 2025
This study is aimed to clarify the effectiveness of the image-rotation technique and zooming augmentation to improve the accuracy of the deep learning (DL)-based dose conversion from pencil beam (PB) to Monte Carlo (MC) in proton beam therapy (PBT). ...
On factors that influence deep learning-based dose prediction of head and neck tumors.
Physics in medicine and biology
May 22, 2025
This study investigates key factors influencing deep learning-based dose prediction models for head and neck cancer radiation therapy. The goal is to evaluate model accuracy, robustness, and computational efficiency, and to identify key components ne...
[Orthodontics in the CBCT era: 25 years later, what are the guidelines?].
L' Orthodontie francaise
May 15, 2025
INTRODUCTION: CBCT has become an essential tool in orthodontics, although its use must remain judicious and evidence-based. This study provides an updated analysis of international recommendations concerning the use of CBCT in orthodontics, with a pa...
Lightweight and universal deep learning model for fast proton spot dose calculation at arbitrary energies.
Physics in medicine and biology
May 13, 2025
To better integrate into processes like rapid adaptive planning and quality assurance, this study aims to propose a lightweight and universal proton spot dose calculation model suitable for arbitrary energies.Given the alignment between the character...
Assessment of Image Quality of Coronary Computed Tomography Angiography in Obese Patients by Comparing Deep Learning Image Reconstruction With Adaptive Statistical Iterative Reconstruction Veo.
Journal of computer assisted tomography
May 13, 2025
OBJECTIVE: The aim of the study was to evaluate the image quality of coronary computed tomography (CT) angiography (CCTA) in obese patients by using deep learning image reconstruction (DLIR) in comparison with adaptive statistical iterative reconstru...
Evaluation of SR-DLR in low-dose abdominal CT: superior image quality and noise reduction.
Abdominal radiology (New York)
May 1, 2025
OBJECTIVES: To evaluate the effectiveness of super-resolution deep learning reconstruction (SR-DLR) in low-dose abdominal computed tomography (CT) imaging compared with hybrid iterative reconstruction (HIR) and conventional deep learning reconstructi...
Effect of adaptive statistical iterative reconstruction-V algorithm and deep learning image reconstruction algorithm on image quality and emphysema quantification in COPD patients under ultra-low-dose conditions.
The British journal of radiology
Apr 1, 2025
PURPOSE: To explore the effect of different reconstruction algorithms (ASIR-V and DLIR) on image quality and emphysema quantification in chronic obstructive pulmonary disease (COPD) patients under ultra-low-dose scanning conditions.
Converting dose-area product to effective dose in dental cone-beam computed tomography using organ-specific deep learning.
Dento maxillo facial radiology
Mar 1, 2025
OBJECTIVE: To develop an accurate method for converting dose-area product (DAP) to patient dose for dental cone-beam computed tomography (CBCT) using deep learning.
State-of-the-Art Deep Learning CT Reconstruction Algorithms in Abdominal Imaging.
Radiographics : a review publication of the Radiological Society of North America, Inc
Dec 1, 2024
The implementation of deep neural networks has spurred the creation of deep learning reconstruction (DLR) CT algorithms. DLR CT techniques encompass a spectrum of deep learning-based methodologies that operate during the different steps of the image ...
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