AIMC Topic: Lung

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Emphysema Progression at CT by Deep Learning Predicts Functional Impairment and Mortality: Results from the COPDGene Study.

Radiology May 17, 2022
Background Visual assessment remains the standard for evaluating emphysema at CT; however, it is time consuming, is subjective, requires training, and is affected by variability that may limit sensitivity to longitudinal change. Purpose To evaluate t...
Pulmonary Emphysema Emphysema Severity of Illness Index Deep Learning Aged Pulmonary Disease, Chronic Obstructive Middle Aged Lung Male Tomography, X-Ray Computed Female Humans Prospective Studies
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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).
Lung Pulmonary Ventilation Tomography, Emission-Computed, Single-Photon Deep Learning Four-Dimensional Computed Tomography Image Processing, Computer-Assisted
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WVALE: Weak variational autoencoder for localisation and enhancement of COVID-19 lung infections.

Computer methods and programs in biomedicine May 14, 2022
BACKGROUND AND OBJECTIVE: The COVID-19 pandemic is a major global health crisis of this century. The use of neural networks with CT imaging can potentially improve clinicians' efficiency in diagnosis. Previous studies in this field have primarily foc...
Pandemics COVID-19 Image Processing, Computer-Assisted Supervised Machine Learning Lung Humans
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MEA-Net: multilayer edge attention network for medical image segmentation.

Scientific reports May 12, 2022
Medical image segmentation is a fundamental step in medical analysis and diagnosis. In recent years, deep learning networks have been used for precise segmentation. Numerous improved encoder-decoder structures have been proposed for various segmentat...
Image Processing, Computer-Assisted Thorax Retinal Vessels Neural Networks, Computer Lung
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Artificial Intelligence (AI) for Lung Nodules, From the Special Series on AI Applications.

AJR. American journal of roentgenology May 11, 2022
Interest in artificial intelligence (AI) applications for lung nodules continues to grow among radiologists, particularly with the expanding eligibility criteria and clinical utilization of lung cancer screening CT. AI has been heavily investigated f...
Early Detection of Cancer Radiologists Humans Lung Artificial Intelligence Lung Neoplasms
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An improved CNN-based architecture for automatic lung nodule classification.

Medical & biological engineering & computing May 7, 2022
Lung cancer is one of the most critical diseases due to its significant death rate compared to all other types of cancer. The early diagnosis of lung cancer that improves the patient's chance of surviving is mostly done in two phases: screening throu...
Lung Neoplasms Lung Diagnosis, Computer-Assisted Neural Networks, Computer Tomography, X-Ray Computed Humans
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Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population.

PloS one May 5, 2022
OBJECTIVE: In this study, we evaluated a commercially available computer assisted diagnosis system (CAD). The deep learning algorithm of the CAD was trained with a lung cancer screening cohort and developed for detection, classification, quantificati...
Radiographic Image Interpretation, Computer-Assisted Sensitivity and Specificity Solitary Pulmonary Nodule Lung Retrospective Studies Humans Deep Learning Early Detection of Cancer Computers Tomography, X-Ray Computed Lung Neoplasms Multiple Pulmonary Nodules
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Deep Learning-Based Classification of Reduced Lung Ultrasound Data From COVID-19 Patients.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control Apr 27, 2022
The application of lung ultrasound (LUS) imaging for the diagnosis of lung diseases has recently captured significant interest within the research community. With the ongoing COVID-19 pandemic, many efforts have been made to evaluate LUS data. A four...
Pandemics COVID-19 Humans Lung Ultrasonography Deep Learning
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Machine Learning for Cardiovascular Biomechanics Modeling: Challenges and Beyond.

Annals of biomedical engineering Apr 20, 2022
Recent progress in machine learning (ML), together with advanced computational power, have provided new research opportunities in cardiovascular modeling. While classifying patient outcomes and medical image segmentation with ML have already shown si...
Humans Lung Cardiovascular System Machine Learning Patient-Specific Modeling Biomechanical Phenomena
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MS-ResNet: disease-specific survival prediction using longitudinal CT images and clinical data.

International journal of computer assisted radiology and surgery Apr 20, 2022
PURPOSE: Medical imaging data of lung cancer in different stages contain a large amount of time information related to its evolution (emergence, development, or extinction). We try to explore the evolution process of lung images in time dimension to ...
Lung Lung Neoplasms Algorithms Tomography, X-Ray Computed Humans Neural Networks, Computer
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