AI Medical Compendium Topic:
Lung

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Quantitative evaluation of COVID-19 pneumonia severity by CT pneumonia analysis algorithm using deep learning technology and blood test results.

Japanese journal of radiology
PURPOSE: To evaluate whether early chest computed tomography (CT) lesions quantified by an artificial intelligence (AI)-based commercial software and blood test values at the initial presentation can differentiate the severity of COVID-19 pneumonia.

A self-supervised feature-standardization-block for cross-domain lung disease classification.

Methods (San Diego, Calif.)
With the advance of deep learning technology, convolutional neural network (CNN) has been wildly used and achieved the state-of-the-art performances in the area of medical image classification. However, most existing medical image classification meth...

Augmenting lung cancer diagnosis on chest radiographs: positioning artificial intelligence to improve radiologist performance.

Clinical radiology
AIM: To evaluate the role that artificial intelligence (AI) could play in assisting radiologists as the first reader of chest radiographs (CXRs), to increase the accuracy and efficiency of lung cancer diagnosis by flagging positive cases before passi...

Hybrid dilation and attention residual U-Net for medical image segmentation.

Computers in biology and medicine
Medical image segmentation is a typical task in medical image processing and critical foundation in medical image analysis. U-Net is well-liked in medical image segmentation, but it doesn't fully explore useful features of the channel and capitalize ...

Multiscale Attention Guided Network for COVID-19 Diagnosis Using Chest X-Ray Images.

IEEE journal of biomedical and health informatics
Coronavirus disease 2019 (COVID-19) is one of the most destructive pandemic after millennium, forcing the world to tackle a health crisis. Automated lung infections classification using chest X-ray (CXR) images could strengthen diagnostic capability ...

Radiologists versus Deep Convolutional Neural Networks: A Comparative Study for Diagnosing COVID-19.

Computational and mathematical methods in medicine
The reverse transcriptase polymerase chain reaction (RT-PCR) is still the routinely used test for the diagnosis of SARS-CoV-2 (COVID-19). However, according to several reports, RT-PCR showed a low sensitivity and multiple tests may be required to rul...

Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.

BMC medical imaging
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...

Thoracic Point-of-Care Ultrasound: A SARS-CoV-2 Data Repository for Future Artificial Intelligence and Machine Learning.

Surgical innovation
Current experience suggests that artificial intelligence (AI) and machine learning (ML) may be useful in the management of hospitalized patients, including those with COVID-19. In light of the challenges faced with diagnostic and prognostic indicator...

Automated Diagnosis of COVID-19 Using Deep Features and Parameter Free BAT Optimization.

IEEE journal of translational engineering in health and medicine
Accurate and fast diagnosis of COVID-19 is very important to manage the medical conditions of affected persons. The task is challenging owing to shortage and ineffectiveness of clinical testing kits. However, the existing problems can be improved by...

NIA-Network: Towards improving lung CT infection detection for COVID-19 diagnosis.

Artificial intelligence in medicine
During pandemics (e.g., COVID-19) physicians have to focus on diagnosing and treating patients, which often results in that only a limited amount of labeled CT images is available. Although recent semi-supervised learning algorithms may alleviate the...