AIMC Topic: X-Rays

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Classification of COVID-19 chest X-Ray and CT images using a type of dynamic CNN modification method.

Computers in biology and medicine
Understanding and classifying Chest X-Ray (CXR) and computerised tomography (CT) images are of great significance for COVID-19 diagnosis. The existing research on the classification for COVID-19 cases faces the challenges of data imbalance, insuffici...

Deep learning model for distinguishing novel coronavirus from other chest related infections in X-ray images.

Computers in biology and medicine
Novel Coronavirus is deadly for humans and animals. The ease of its dispersion, coupled with its tremendous capability for ailment and death in infected people, makes it a risk to society. The chest X-ray is conventional but hard to interpret radiogr...

DenseCapsNet: Detection of COVID-19 from X-ray images using a capsule neural network.

Computers in biology and medicine
At present, the global pandemic as it relates to novel coronavirus pneumonia is still a very difficult situation. Due to the recent outbreak of novel coronavirus pneumonia, novel chest X-ray (CXR) images that can be used for deep learning analysis ar...

BS-Net: Learning COVID-19 pneumonia severity on a large chest X-ray dataset.

Medical image analysis
In this work we design an end-to-end deep learning architecture for predicting, on Chest X-rays images (CXR), a multi-regional score conveying the degree of lung compromise in COVID-19 patients. Such semi-quantitative scoring system, namely Brixia sc...

A Cascade-SEME network for COVID-19 detection in chest x-ray images.

Medical physics
PURPOSE: The worldwide spread of the SARS-CoV-2 virus poses unprecedented challenges to medical resources and infection prevention and control measures around the world. In this case, a rapid and effective detection method for COVID-19 can not only r...

Image-based deep learning in diagnosing the etiology of pneumonia on pediatric chest X-rays.

Pediatric pulmonology
PURPOSE: Comparing the efficacy of a deep-learning model in classifying the etiology of pneumonia on pediatric chest X-rays (CXRs) with that of human readers.

Role of Hybrid Deep Neural Networks (HDNNs), Computed Tomography, and Chest X-rays for the Detection of COVID-19.

International journal of environmental research and public health
COVID-19 syndrome has extensively escalated worldwide with the induction of the year 2020 and has resulted in the illness of millions of people. COVID-19 patients bear an elevated risk once the symptoms deteriorate. Hence, early recognition of diseas...

Exploring the effect of image enhancement techniques on COVID-19 detection using chest X-ray images.

Computers in biology and medicine
Computer-aided diagnosis for the reliable and fast detection of coronavirus disease (COVID-19) has become a necessity to prevent the spread of the virus during the pandemic to ease the burden on the healthcare system. Chest X-ray (CXR) imaging has se...

COVID-19 Recognition Using Ensemble-CNNs in Two New Chest X-ray Databases.

Sensors (Basel, Switzerland)
The recognition of COVID-19 infection from X-ray images is an emerging field in the learning and computer vision community. Despite the great efforts that have been made in this field since the appearance of COVID-19 (2019), the field still suffers f...