AIMC Topic: Emphysema

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COPD identification and grading based on deep learning of lung parenchyma and bronchial wall in chest CT images.

The British journal of radiology Feb 16, 2022
OBJECTIVE: Chest CT can display the main pathogenic factors of chronic obstructive pulmonary disease (COPD), emphysema and airway wall remodeling. This study aims to establish deep convolutional neural network (CNN) models using these two imaging mar...
Deep Learning Pulmonary Emphysema Emphysema Pulmonary Disease, Chronic Obstructive Lung Humans Retrospective Studies Tomography, X-Ray Computed
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Using machine learning algorithms to review computed tomography scans and assess risk for cardiovascular disease: Retrospective analysis from the National Lung Screening Trial (NLST).

PloS one Aug 3, 2020
BACKGROUND: The National Lung Screening Trial (NLST) demonstrated that annual screening with low dose CT in high-risk population was associated with reduction in lung cancer mortality. Nonetheless, the leading cause of mortality in the study was from...
National Cancer Institute (U.S.) Emphysema Cigarette Smoking Coronary Vessels Clinical Trials, Phase III as Topic Randomized Controlled Trials as Topic Radiographic Image Interpretation, Computer-Assisted Machine Learning Retrospective Studies Lung Neoplasms Tomography, X-Ray Computed Fatty Liver Female United States Risk Factors Middle Aged Mass Screening Early Detection of Cancer Humans Risk Assessment Liver Lung Male Cardiovascular Diseases
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Semi-Supervised Learning for Semantic Segmentation of Emphysema With Partial Annotations.

IEEE journal of biomedical and health informatics Dec 31, 2019
Segmentation and quantification of each subtype of emphysema is helpful to monitor chronic obstructive pulmonary disease. Due to the nature of emphysema (diffuse pulmonary disease), it is very difficult for experts to allocate semantic labels to ever...
Male Tomography, X-Ray Computed Humans Lung Radiographic Image Interpretation, Computer-Assisted Female Deep Learning Supervised Machine Learning Emphysema
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Classification of Volumetric Images Using Multi-Instance Learning and Extreme Value Theorem.

IEEE transactions on medical imaging Aug 19, 2019
Volumetric imaging is an essential diagnostic tool for medical practitioners. The use of popular techniques such as convolutional neural networks (CNN) for analysis of volumetric images is constrained by the availability of detailed (with local annot...
Deep Learning Tomography, X-Ray Computed Humans Imaging, Three-Dimensional Algorithms Supervised Machine Learning Pulmonary Disease, Chronic Obstructive Emphysema Lung
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Deep Learning-Based Kernel Adaptation Enhances Quantification of Emphysema on Low-Dose Chest CT for Predicting Long-Term Mortality.

Investigative radiology Mar 1, 2024
OBJECTIVES: The aim of this study was to ascertain the predictive value of quantifying emphysema using low-dose computed tomography (LDCT) post deep learning-based kernel adaptation on long-term mortality.
Humans Retrospective Studies Deep Learning Pulmonary Emphysema Emphysema Tomography, X-Ray Computed Male Lung
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The Promise of Quantitative Computed Tomographic Analysis in Assessing Progression of Interstitial Lung Abnormalities and Emphysema in Smokers.

American journal of respiratory and critical care medicine Sep 15, 2023
Humans Emphysema Lung Diseases, Interstitial Pulmonary Emphysema Smokers Lung Deep Learning
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Deep Learning Assessment of Progression of Emphysema and Fibrotic Interstitial Lung Abnormality.

American journal of respiratory and critical care medicine Sep 15, 2023
Although studies have evaluated emphysema and fibrotic interstitial lung abnormality individually, less is known about their combined progression. To define clinically meaningful progression of fibrotic interstitial lung abnormality in smokers with...
Emphysema Humans Lung Diseases, Interstitial Lung Pulmonary Emphysema Deep Learning Pulmonary Fibrosis
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ACRnet: Adaptive Cross-transfer Residual neural network for chest X-ray images discrimination of the cardiothoracic diseases.

Mathematical biosciences and engineering : MBE May 7, 2022
Cardiothoracic diseases are a serious threat to human health and chest X-ray image is a great reference in diagnosis and treatment. At present, it has been a research hot-spot how to recognize chest X-ray image automatically and exactly by the comput...
X-Rays Emphysema Humans Neural Networks, Computer Cardiomegaly
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[Quantitative Analysis of Emphysema in Ultra-high-resolution CT by Using Deep Learning Reconstruction: Comparison with Hybrid Iterative Reconstruction].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2020
PURPOSE: The noise generated in ultra-high-resolution computed tomography (U-HRCT) images affects the quantitative analysis of emphysema. In this study, we compared the physical properties of reconstructed images for hybrid iterative reconstruction (...
Radiation Dosage Emphysema Deep Learning Radiographic Image Interpretation, Computer-Assisted Humans Algorithms Tomography, X-Ray Computed
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