AIMC Topic: Radiation Dosage
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Emphysema quantification using low-dose computed tomography with deep learning-based kernel conversion comparison.
European radiology
Jun 29, 2020
OBJECTIVE: This study determined the effect of dose reduction and kernel selection on quantifying emphysema using low-dose computed tomography (LDCT) and evaluated the efficiency of a deep learning-based kernel conversion technique in normalizing ker...
Task-based characterization of a deep learning image reconstruction and comparison with filtered back-projection and a partial model-based iterative reconstruction in abdominal CT: A phantom 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)
Jun 20, 2020
PURPOSE: We aimed to thoroughly characterize image quality of a novel deep learning image reconstruction (DLIR), and investigate its potential for dose reduction in abdominal CT in comparison with filtered back-projection (FBP) and a partial model-ba...
Estimation of glandular dose in mammography based on artificial neural networks.
Physics in medicine and biology
May 11, 2020
This work proposes using artificial neural networks (ANNs) for the regression of the dosimetric quantities employed in mammography. The data were generated by Monte Carlo (MC) simulations using a modified and validated version of the PENELOPE (v. 201...
Error detection using a convolutional neural network with dose difference maps in patient-specific quality assurance for volumetric modulated arc therapy.
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)
Apr 21, 2020
The aim of this study was to evaluate the use of dose difference maps with a convolutional neural network (CNN) to detect multi-leaf collimator (MLC) positional errors in patient-specific quality assurance for volumetric modulated radiation therapy (...
Conventional vs machine learning-based treatment planning in prostate brachytherapy: Results of a Phase I randomized controlled trial.
Brachytherapy
Apr 19, 2020
PURPOSE: The purpose of this study was to evaluate the noninferiority of Day 30 dosimetry between a machine learning-based treatment planning system for prostate low-dose-rate (LDR) brachytherapy and the conventional, manual planning technique. As a ...
Image Quality Assessment of Abdominal CT by Use of New Deep Learning Image Reconstruction: Initial Experience.
AJR. American journal of roentgenology
Apr 14, 2020
The purpose of this study was to perform quantitative and qualitative evaluation of a deep learning image reconstruction (DLIR) algorithm in contrast-enhanced oncologic CT of the abdomen. Retrospective review (April-May 2019) of the cases of adults...
DeepDose: Towards a fast dose calculation engine for radiation therapy using deep learning.
Physics in medicine and biology
Apr 8, 2020
We present DeepDose, a deep learning framework for fast dose calculations in radiation therapy. Given a patient anatomy and linear-accelerator IMRT multi-leaf-collimator shape or segment, a novel set of physics-based inputs is calculated that encode ...
A convolution neural network for higher resolution dose prediction in prostate volumetric modulated arc therapy.
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)
Apr 1, 2020
PURPOSE: This study aims to investigate the feasibility of using convolutional neural networks to predict an accurate and high resolution dose distribution from an approximated and low resolution input dose.
Evaluation of a neural network-based photon beam profile deconvolution method.
Journal of applied clinical medical physics
Mar 30, 2020
PURPOSE: The authors have previously shown the feasibility of using an artificial neural network (ANN) to eliminate the volume average effect (VAE) of scanning ionization chambers (ICs). The purpose of this work was to evaluate the method when applie...
Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.
European radiology
Feb 25, 2020
OBJECTIVES: To assess the impact on image quality and dose reduction of a new deep learning image reconstruction (DLIR) algorithm compared with a hybrid iterative reconstruction (IR) algorithm.
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