AIMC Topic: Radiography, Thoracic

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Pneumonia detection on chest X-rays from Xception-based transfer learning and logistic regression.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2024
Pneumonia is a dangerous disease that kills millions of children and elderly patients worldwide every year. The detection of pneumonia from a chest x-ray is perpetrated by expert radiologists. The chest x-ray is cheaper and is most often used to diag...
Pneumonia SARS-CoV-2 Radiography, Thoracic Logistic Models Support Vector Machine Humans Machine Learning COVID-19
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Can AI generate diagnostic reports for radiologist approval on CXR images? A multi-reader and multi-case observer performance study.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Accurately detecting a variety of lung abnormalities from heterogenous chest X-ray (CXR) images and writing radiology reports is often difficult and time-consuming.
Aged Young Adult Adult Radiography, Thoracic Artificial Intelligence Sensitivity and Specificity Radiographic Image Interpretation, Computer-Assisted Retrospective Studies Lung Diseases Lung Female Male Observer Variation Adolescent Radiologists Humans Middle Aged
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Classification of Pneumonia via a Hybrid ZFNet-Quantum Neural Network Using a Chest X-ray Dataset.

Current medical imaging Jan 1, 2024
INTRODUCTION: Deep neural networks (DNNs) have made significant contributions to diagnosing pneumonia from chest X-ray imaging. However, certain aspects of diagnosis and planning can be further enhanced through the implementation of a quantum deep ne...
Radiography, Thoracic Humans Algorithms Neural Networks, Computer Deep Learning Pneumonia
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Multi-disease X-ray Image Classification of the Chest Based on Global and Local Fusion Adaptive Networks.

Current medical imaging Jan 1, 2024
BACKGROUND: Chest X-ray image classification for multiple diseases is an important research direction in the field of computer vision and medical image processing. It aims to utilize advanced image processing techniques and deep learning algorithms t...
Radiographic Image Interpretation, Computer-Assisted Radiography, Thoracic Algorithms Deep Learning Image Processing, Computer-Assisted Humans Neural Networks, Computer
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Hemi-diaphragm detection of chest X-ray images based on convolutional neural network and graphics.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: Chest X-rays (CXR) are widely used to facilitate the diagnosis and treatment of critically ill and emergency patients in clinical practice. Accurate hemi-diaphragm detection based on postero-anterior (P-A) CXR images is crucial for the di...
Diaphragm Humans Neural Networks, Computer Lung Diseases Radiography, Thoracic
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Artificial intelligence's contribution to early pulmonary lesion detection in chest X-rays: insights from two retrospective studies on a Czech population.

Casopis lekaru ceskych Jan 1, 2024
In recent years healthcare is undergoing significant changes due to technological innovations, with Artificial Intelligence (AI) being a key trend. Particularly in radiodiagnostics, according to studies, AI has the potential to enhance accuracy and e...
Retrospective Studies Sensitivity and Specificity Deep Learning Humans Artificial Intelligence Radiography, Thoracic Lung Neoplasms Early Detection of Cancer Czech Republic
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Predicting patient-specific organ doses from thoracic CT examinations using support vector regression algorithm.

Journal of X-ray science and technology Jan 1, 2024
PURPOSE: This study aims to propose and develop a fast, accurate, and robust prediction method of patient-specific organ doses from CT examinations using minimized computational resources.
Humans Algorithms Lung Support Vector Machine Radiation Dosage Radiography, Thoracic Monte Carlo Method Adult Male Middle Aged Tomography, X-Ray Computed Female Aged
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DDA-SSNets: Dual decoder attention-based semantic segmentation networks for COVID-19 infection segmentation and classification using chest X-Ray images.

Journal of X-ray science and technology Jan 1, 2024
BACKGROUND: COVID-19 needs to be diagnosed and staged to be treated accurately. However, prior studies' diagnostic and staging abilities for COVID-19 infection needed to be improved. Therefore, new deep learning-based approaches are required to aid r...
Algorithms SARS-CoV-2 Lung Neural Networks, Computer Pandemics COVID-19 Radiography, Thoracic Betacoronavirus Pneumonia, Viral Deep Learning Coronavirus Infections Semantics Humans
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Commercially Available Chest Radiograph AI Tools for Detecting Airspace Disease, Pneumothorax, and Pleural Effusion.

Radiology Sep 1, 2023
Background Commercially available artificial intelligence (AI) tools can assist radiologists in interpreting chest radiographs, but their real-life diagnostic accuracy remains unclear. Purpose To evaluate the diagnostic accuracy of four commercially ...
Pleural Effusion Radiography, Thoracic Pneumothorax Adult Sensitivity and Specificity Deep Learning Humans Artificial Intelligence Retrospective Studies Female Aged
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Deep Learning-Enabled Detection of Pneumoperitoneum in Supine and Erect Abdominal Radiography: Modeling Using Transfer Learning and Semi-Supervised Learning.

Korean journal of radiology Jun 1, 2023
OBJECTIVE: Detection of pneumoperitoneum using abdominal radiography, particularly in the supine position, is often challenging. This study aimed to develop and externally validate a deep learning model for the detection of pneumoperitoneum using sup...
Radiography, Abdominal Radiography Supervised Machine Learning Radiography, Thoracic Humans Retrospective Studies Deep Learning
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