AIMC Topic: Pulmonary Ventilation

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CT ventilation images produced by a 3D neural network show improvement over the Jacobian and HU DIR-based methods to predict quantized lung function.

Medical physics Nov 23, 2024
BACKGROUND: Radiation-induced pneumonitis affects up to 33% of non-small cell lung cancer (NSCLC) patients, with fatal pneumonitis occurring in 2% of patients. Pneumonitis risk is related to the dose and volume of lung irradiated. Clinical radiothera...
Humans Neural Networks, Computer Tomography, X-Ray Computed Lung Neoplasms Lung Carcinoma, Non-Small-Cell Lung Imaging, Three-Dimensional Pulmonary Ventilation
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A hybrid model- and deep learning-based framework for functional lung image synthesis from multi-inflation CT and hyperpolarized gas MRI.

Medical physics Apr 1, 2023
BACKGROUND: Hyperpolarized gas MRI is a functional lung imaging modality capable of visualizing regional lung ventilation with exceptional detail within a single breath. However, this modality requires specialized equipment and exogenous contrast, wh...
Magnetic Resonance Imaging Humans Pulmonary Ventilation Lung Deep Learning Tomography, X-Ray Computed
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A deep learning method for translating 3DCT to SPECT ventilation imaging: First comparison with Kr-gas SPECT ventilation imaging.

Medical physics May 17, 2022
PURPOSE: This study aimed to evaluate the accuracy of deep learning (DL)-based computed tomography (CT) ventilation imaging (CTVI).
Four-Dimensional Computed Tomography Image Processing, Computer-Assisted Pulmonary Ventilation Lung Tomography, Emission-Computed, Single-Photon Deep Learning
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Functional Lung MRI: Deep Learning Turns Proton into Helium Ventilation Maps-The Battle Is On!

Radiology Dec 8, 2020
Helium Pulmonary Ventilation Protons Deep Learning Magnetic Resonance Imaging Humans Lung
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Pulmonary Ventilation Maps Generated with Free-breathing Proton MRI and a Deep Convolutional Neural Network.

Radiology Dec 8, 2020
Background Hyperpolarized noble gas MRI helps measure lung ventilation, but clinical translation remains limited. Free-breathing proton MRI may help quantify lung function using existing MRI systems without contrast material and may assist in providi...
Male Middle Aged Lung Aged Adult Image Interpretation, Computer-Assisted Pulmonary Ventilation Protons Magnetic Resonance Imaging Lung Diseases Humans Prospective Studies Female Neural Networks, Computer
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A deep learning method for producing ventilation images from 4DCT: First comparison with technegas SPECT ventilation.

Medical physics Jan 28, 2020
PURPOSE: The purpose of this study is to develop a deep learning (DL) method for producing four-dimensional computed tomography (4DCT) ventilation imaging and to evaluate the accuracy of the DL-based ventilation imaging against single-photon emission...
Pulmonary Ventilation Tomography, Emission-Computed, Single-Photon Humans Four-Dimensional Computed Tomography Deep Learning Image Processing, Computer-Assisted
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Machine Learning Reveals the Texture of Regional Lung Ventilation at CT.

Radiology Oct 22, 2019
Humans Machine Learning Pulmonary Disease, Chronic Obstructive Tomography, X-Ray Computed Pulmonary Ventilation
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Chronic Obstructive Pulmonary Disease: Thoracic CT Texture Analysis and Machine Learning to Predict Pulmonary Ventilation.

Radiology Oct 22, 2019
Background Fixed airflow limitation and ventilation heterogeneity are common in chronic obstructive pulmonary disease (COPD). Conventional noncontrast CT provides airway and parenchymal measurements but cannot be used to directly determine lung funct...
Pulmonary Disease, Chronic Obstructive Male Support Vector Machine Longitudinal Studies Middle Aged Aged Aged, 80 and over Adult Humans Tomography, X-Ray Computed Machine Learning Female Prospective Studies Magnetic Resonance Imaging Pulmonary Ventilation
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Expert-level classification of ventilatory thresholds from cardiopulmonary exercising test data with recurrent neural networks.

European journal of sport science Mar 18, 2019
First and second ventilatory thresholds (VT and VT) represent the boundaries of the moderate-heavy and heavy-severe exercise intensity. Currently, VTs are primarily detected visually from cardiopulmonary exercise test (CPET) data, beginning with an i...
Artificial Intelligence Pulmonary Ventilation Humans Exercise Test Anaerobic Threshold Neural Networks, Computer
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Technical Note: Deriving ventilation imaging from 4DCT by deep convolutional neural network.

Medical physics Mar 12, 2019
PURPOSE: Ventilation images can be derived from four-dimensional computed tomography (4DCT) by analyzing the change in HU values and deformable vector fields between different respiration phases of computed tomography (CT). As deformable image regist...
Deep Learning Humans Pulmonary Ventilation Image Processing, Computer-Assisted Four-Dimensional Computed Tomography
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