AIMC Topic: Lung

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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...

Deep Convolutional Neural Network-Based Computer-Aided Detection System for COVID-19 Using Multiple Lung Scans: Design and Implementation Study.

Journal of medical Internet research
BACKGROUND: Owing to the COVID-19 pandemic and the imminent collapse of health care systems following the exhaustion of financial, hospital, and medicinal resources, the World Health Organization changed the alert level of the COVID-19 pandemic from ...

Prediction of COVID-19 with Computed Tomography Images using Hybrid Learning Techniques.

Disease markers
Reverse Transcription Polymerase Chain Reaction (RT-PCR) used for diagnosing COVID-19 has been found to give low detection rate during early stages of infection. Radiological analysis of CT images has given higher prediction rate when compared to RT-...

Crowdsourcing airway annotations in chest computed tomography images.

PloS one
Measuring airways in chest computed tomography (CT) scans is important for characterizing diseases such as cystic fibrosis, yet very time-consuming to perform manually. Machine learning algorithms offer an alternative, but need large sets of annotate...

Deep learning in structural and functional lung image analysis.

The British journal of radiology
The recent resurgence of deep learning (DL) has dramatically influenced the medical imaging field. Medical image analysis applications have been at the forefront of DL research efforts applied to multiple diseases and organs, including those of the l...