A deep learning-based framework for detecting COVID-19 patients using chest X-rays
Sign Up to like & getrecommendations! Published in 2022 at "Multimedia Systems"
DOI: 10.1007/s00530-022-00917-7
Abstract: Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has caused outbreaks of new coronavirus disease (COVID-19) around the world. Rapid and accurate detection of COVID-19 coronavirus is an important step in limiting the spread of the… read more here.
Keywords: deep learning; chest rays; covid patients; detecting covid ... See more keywords
Chest X-rays of newborns in a medical facility: variation between the entrance skin dose measurements using the indirect and direct methods for clinical dose audit
Sign Up to like & getrecommendations! Published in 2021 at "Japanese Journal of Radiology"
DOI: 10.1007/s11604-021-01193-7
Abstract: This study aims to determine the mean and 75th percentile entrance skin dose (ESDcal) from anteroposterior (AP) chest X-rays using machine parameters (indirect method). Also, a comparison was made between the ESDcal and already determined… read more here.
Keywords: indirect direct; skin dose; chest rays; radiology ... See more keywords
Application of deep learning to identify COVID-19 infection in posteroanterior chest X-rays
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DOI: 10.1016/j.clinimag.2021.07.004
Abstract: Introduction Posteroanterior chest X-rays (CXRs) are recommended over computed tomography scans for COVID-19 diagnosis, as CXRs can be obtained with relatively low risk of facility contamination. The objective of this study was to assess seven… read more here.
Keywords: classification; posteroanterior chest; chest rays; cxrs ... See more keywords
Detection of respiratory diseases from chest X rays using Nesterov accelerated adaptive moment estimation
Sign Up to like & getrecommendations! Published in 2021 at "Measurement"
DOI: 10.1016/j.measurement.2021.109153
Abstract: Abstract Recent developments in the field of machine learning have led to drastic improvements in medical diagnosis. Identification of different medical conditions with high accuracy is possible through machine learning, specifically deep learning. Convolutional Neural… read more here.
Keywords: detection respiratory; accuracy; neural networks; diseases chest ... See more keywords
Interpreting Chest X-rays via CNNs that Exploit Hierarchical Disease Dependencies and Uncertainty Labels
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DOI: 10.1016/j.neucom.2020.03.127
Abstract: Chest radiography is one of the most common types of diagnostic radiology exams, which is critical for screening and diagnosis of many different thoracic diseases. Specialized algorithms have been developed to detect several specific pathologies… read more here.
Keywords: interpreting chest; chest rays; rays via; cnns exploit ... See more keywords
GraphXCOVID: Explainable deep graph diffusion pseudo-Labelling for identifying COVID-19 on chest X-rays
Sign Up to like & getrecommendations! Published in 2021 at "Pattern Recognition"
DOI: 10.1016/j.patcog.2021.108274
Abstract: Can one learn to diagnose COVID-19 under extreme minimal supervision? Since the outbreak of the novel COVID-19 there has been a rush for developing automatic techniques for expert-level disease identification on Chest X-ray data. In… read more here.
Keywords: graph diffusion; diffusion; chest; identifying covid ... See more keywords
Comparison of Gray-scale Inversion to Improve Detection of Pulmonary Nodules on Chest X-rays Between Radiologists and a Deep Convolutional Neural Network.
Sign Up to like & getrecommendations! Published in 2022 at "Current problems in diagnostic radiology"
DOI: 10.1067/j.cpradiol.2022.11.004
Abstract: Detection of pulmonary nodules on chest x-rays is an important task for radiologists. Previous studies have shown improved detection rates using gray-scale inversion. The purpose of our study was to compare the efficacy of gray-scale… read more here.
Keywords: scale inversion; detection pulmonary; chest rays; gray scale ... See more keywords
Intelligent Pneumonia Identification From Chest X-Rays: A Systematic Literature Review
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DOI: 10.1109/access.2021.3069937
Abstract: Chest radiography is a significant diagnostic tool used to detect diseases afflicting the chest. The automatic detection techniques associated with computer vision are being adopted in medical imaging research. Over the last decade, several remarkable… read more here.
Keywords: review; pneumonia identification; pneumonia; intelligent pneumonia ... See more keywords
Convolution Neural Network With Coordinate Attention for the Automatic Detection of Pulmonary Tuberculosis Images on Chest X-Rays
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DOI: 10.1109/access.2022.3199419
Abstract: Tuberculosis is a chronic respiratory infectious disease that seriously endangers human health. Diagnosis of pulmonary tuberculosis usually depend on the analysis of chest X-rays by radiologists. However, there is a certain misdiagnosis rate with time… read more here.
Keywords: neural network; tuberculosis; pulmonary tuberculosis; tuberculosis images ... See more keywords
A Dual-Branch Network for Diagnosis of Thorax Diseases From Chest X-Rays
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DOI: 10.1109/jbhi.2022.3215694
Abstract: Automated chest X-ray analysis has a great potential for diagnosing thorax diseases since errors in diagnosis have always been a concern among radiologists. Being a multi-label classification problem, achieving accurate classification remains challenging. Several studies… read more here.
Keywords: network; lung regions; classification; dual branch ... See more keywords
Viral Pneumonia Screening on Chest X-Rays Using Confidence-Aware Anomaly Detection
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Medical Imaging"
DOI: 10.1109/tmi.2020.3040950
Abstract: Clusters of viral pneumonia occurrences over a short period may be a harbinger of an outbreak or pandemic. Rapid and accurate detection of viral pneumonia using chest X-rays can be of significant value for large-scale… read more here.
Keywords: pneumonia; confidence; anomaly detection; viral pneumonia ... See more keywords