AI Medical Compendium Topic

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X-Rays

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Unsupervised Learning with Generative Adversarial Network for Automatic Tire Defect Detection from X-ray Images.

Sensors (Basel, Switzerland)
Automatic defect detection of tire has become an essential issue in the tire industry. However, it is challenging to inspect the inner structure of tire by surface detection. Therefore, an X-ray image sensor is used for tire defect inspection. At pre...

Application of deep learning neural network in predicting bone mineral density from plain X-ray radiography.

Archives of osteoporosis
UNLABELLED: DeepDXA is a deep learning model designed to infer bone mineral density data from plain pelvis X-ray, and it can achieve good predicted value for clinical use.

AI-based diagnosis of COVID-19 patients using X-ray scans with stochastic ensemble of CNNs.

Physical and engineering sciences in medicine
According to the World Health Organization (WHO), novel coronavirus (COVID-19) is an infectious disease and has a significant social and economic impact. The main challenge in fighting against this disease is its scale. Due to the outbreak, medical f...

Detection and analysis of COVID-19 in medical images using deep learning techniques.

Scientific reports
The main purpose of this work is to investigate and compare several deep learning enhanced techniques applied to X-ray and CT-scan medical images for the detection of COVID-19. In this paper, we used four powerful pre-trained CNN models, VGG16, Dense...

Generalized Zero-Shot Chest X-Ray Diagnosis Through Trait-Guided Multi-View Semantic Embedding With Self-Training.

IEEE transactions on medical imaging
Zero-shot learning (ZSL) is one of the most promising avenues of annotation-efficient machine learning. In the era of deep learning, ZSL techniques have achieved unprecedented success. However, the developments of ZSL methods have taken place mostly ...

Determining Top Fully Connected Layer's Hidden Neuron Count for Transfer Learning, Using Knowledge Distillation: a Case Study on Chest X-Ray Classification of Pneumonia and COVID-19.

Journal of digital imaging
Deep convolutional neural network (CNN)-assisted classification of images is one of the most discussed topics in recent years. Continuously innovation of neural network architectures is making it more correct and efficient every day. But training a n...

Detection of COVID-19 in Chest X-ray Images: A Big Data Enabled Deep Learning Approach.

International journal of environmental research and public health
Coronavirus disease (COVID-19) spreads from one person to another rapidly. A recently discovered coronavirus causes it. COVID-19 has proven to be challenging to detect and cure at an early stage all over the world. Patients showing symptoms of COVID-...

Detection of COVID-19 from Chest X-ray Images Using Deep Convolutional Neural Networks.

Sensors (Basel, Switzerland)
The COVID-19 global pandemic has wreaked havoc on every aspect of our lives. More specifically, healthcare systems were greatly stretched to their limits and beyond. Advances in artificial intelligence have enabled the implementation of sophisticated...

Deep learning-based reconstruction of interventional tools and devices from four X-ray projections for tomographic interventional guidance.

Medical physics
PURPOSE: Image guidance for minimally invasive interventions is usually performed by acquiring fluoroscopic images using a monoplanar or a biplanar C-arm system. However, the projective data provide only limited information about the spatial structur...

Detection of COVID-19 Using Transfer Learning and Grad-CAM Visualization on Indigenously Collected X-ray Dataset.

Sensors (Basel, Switzerland)
The COVID-19 outbreak began in December 2019 and has dreadfully affected our lives since then. More than three million lives have been engulfed by this newest member of the corona virus family. With the emergence of continuously mutating variants of ...