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 Carcinoma, Non-Small-Cell Lung Pulmonary Ventilation Lung Imaging, Three-Dimensional
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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 Pulmonary Ventilation Humans 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 Lung Pulmonary Ventilation Deep Learning Tomography, Emission-Computed, Single-Photon
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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 Prospective Studies Female Neural Networks, Computer Humans
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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 Four-Dimensional Computed Tomography Humans 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 Tomography, X-Ray Computed Pulmonary Disease, Chronic Obstructive 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...
Humans Pulmonary Disease, Chronic Obstructive Machine Learning Aged Male Prospective Studies Support Vector Machine Magnetic Resonance Imaging Aged, 80 and over Longitudinal Studies Tomography, X-Ray Computed Middle Aged Pulmonary Ventilation Adult Female
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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 Humans Pulmonary Ventilation Exercise Test Neural Networks, Computer Anaerobic Threshold
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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...
Pulmonary Ventilation Deep Learning Four-Dimensional Computed Tomography Humans Image Processing, Computer-Assisted
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