AIMC Topic: Lung

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Automatic deep learning-based consolidation/collapse classification in lung ultrasound images for COVID-19 induced pneumonia.

Scientific reports Oct 20, 2022
Our automated deep learning-based approach identifies consolidation/collapse in LUS images to aid in the identification of late stages of COVID-19 induced pneumonia, where consolidation/collapse is one of the possible associated pathologies. A common...
Algorithms Lung Humans COVID-19 Deep Learning Ultrasonography
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Deep learning-based classification for lung opacities in chest x-ray radiographs through batch control and sensitivity regulation.

Scientific reports Oct 20, 2022
In this study, we implemented a system to classify lung opacities from frontal chest x-ray radiographs. We also proposed a training method to address the class imbalance problem presented in the dataset. We participated in the Radiological Society of...
Humans Neural Networks, Computer Lung X-Rays Deep Learning Pneumonia
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Automated system for classification of COVID-19 infection from lung CT images based on machine learning and deep learning techniques.

Scientific reports Oct 18, 2022
The objectives of our proposed study were as follows: First objective is to segment the CT images using a k-means clustering algorithm for extracting the region of interest and to extract textural features using gray level co-occurrence matrix (GLCM)...
Deep Learning Machine Learning Bayes Theorem Humans COVID-19 Tomography, X-Ray Computed Lung
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A novel adaptive cubic quasi-Newton optimizer for deep learning based medical image analysis tasks, validated on detection of COVID-19 and segmentation for COVID-19 lung infection, liver tumor, and optic disc/cup.

Medical physics Oct 6, 2022
BACKGROUND: Most of existing deep learning research in medical image analysis is focused on networks with stronger performance. These networks have achieved success, while their architectures are complex and even contain massive parameters ranging fr...
Humans Neural Networks, Computer Deep Learning Image Processing, Computer-Assisted Optic Disk COVID-19 Lung
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Deep learning models for COVID-19 chest x-ray classification: Preventing shortcut learning using feature disentanglement.

PloS one Oct 6, 2022
In response to the COVID-19 global pandemic, recent research has proposed creating deep learning based models that use chest radiographs (CXRs) in a variety of clinical tasks to help manage the crisis. However, the size of existing datasets of CXRs f...
Radiography, Thoracic X-Rays Lung Deep Learning Humans COVID-19
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Artificial Intelligence in Lung Imaging.

Seminars in respiratory and critical care medicine Sep 29, 2022
Recently, interest and advances in artificial intelligence (AI) including deep learning for medical images have surged. As imaging plays a major role in the assessment of pulmonary diseases, various AI algorithms have been developed for chest imaging...
Radiologists Diagnostic Imaging Radiology Artificial Intelligence Lung Humans
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Characterizing Subjects Exposed to Humidifier Disinfectants Using Computed-Tomography-Based Latent Traits: A Deep Learning Approach.

International journal of environmental research and public health Sep 20, 2022
Around nine million people have been exposed to toxic humidifier disinfectants (HDs) in Korea. HD exposure may lead to HD-associated lung injuries (HDLI). However, many people who have claimed that they experienced HD exposure were not diagnosed with...
Male Humidifiers Humans Republic of Korea Lung Deep Learning Tomography, X-Ray Computed Female Disinfectants
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ASO Author Reflections: The Clinical Use of Radiomics with Artificial Intelligence in Patients with Early-Stage Lung Cancer.

Annals of surgical oncology Sep 13, 2022
Humans Lung Neoplasms Artificial Intelligence Thorax Lung
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Unsupervised machine learning identifies predictive progression markers of IPF.

European radiology Sep 6, 2022
OBJECTIVES: To identify and evaluate predictive lung imaging markers and their pathways of change during progression of idiopathic pulmonary fibrosis (IPF) from sequential data of an IPF cohort. To test if these imaging markers predict outcome.
Disease Progression Humans Unsupervised Machine Learning Lung Idiopathic Pulmonary Fibrosis Tomography, X-Ray Computed
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A deep learning approach to generate synthetic CT in low field MR-guided radiotherapy for lung cases.

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology Sep 5, 2022
INTRODUCTION: This study aims to apply a conditional Generative Adversarial Network (cGAN) to generate synthetic Computed Tomography (sCT) from 0.35 Tesla Magnetic Resonance (MR) images of the thorax.
Radiotherapy Planning, Computer-Assisted Radiotherapy Dosage Thorax Radiotherapy, Image-Guided Deep Learning Magnetic Resonance Imaging Tomography, X-Ray Computed Lung Humans
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