AIMC Topic: X-Rays

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Automated Needle Targeting with X-ray (ANT-X) - Robot-assisted device for percutaneous nephrolithotomy (PCNL) with its first successful use in human.

Journal of endourology Jun 1, 2021
INTRODUCTION: To make percutaneous access easier in PCNL, we developed Automated Needle Targeting with X-ray (ANT-X).
Nephrostomy, Percutaneous X-Rays Robotics Punctures Kidney Calculi Nephrolithotomy, Percutaneous Animals Humans Swine
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[Automation of Damage Detection and Damage Area Measurement of X-ray Protective Clothing Using Deep Learning].

Nihon Hoshasen Gijutsu Gakkai zasshi Jan 1, 2021
PURPOSE: Damage to shielding sheets on X-ray protective clothing may be a cause of increased radiation exposure. To prevent increased radiation exposure, periodic quality control of shielding sheets is needed. For quality management, a record of the ...
Deep Learning Radiography Protective Clothing Automation X-Rays
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Tuberculosis detection in chest X-ray using Mayfly-algorithm optimized dual-deep-learning features.

Journal of X-ray science and technology Jan 1, 2021
World-Health-Organization (WHO) has listed Tuberculosis (TB) as one among the top 10 reasons for death and an early diagnosis will help to cure the patient by giving suitable treatment. TB usually affects the lungs and an accurate bio-imaging scheme ...
Ephemeroptera X-Rays Algorithms Humans Deep Learning Animals Tuberculosis
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[Cephalometric analysis of lateral skull X-ray images using soft computing components in the search for key points].

Stomatologiia Jan 1, 2021
THE AIM OF THE STUDY: Was to investigate the efficiency of decoding teleradiological studies using an algorithm based on the use of convolutional neural networks - a simple convolutional architecture, as well as an extended U-Net architecture.
X-Rays Skull Neural Networks, Computer Image Processing, Computer-Assisted Radiography Cephalometry Humans
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Hierarchical convolutional models for automatic pneu-monia diagnosis based on X-ray images: new strategies in public health.

Annali di igiene : medicina preventiva e di comunita Jan 1, 2021
CONCLUSIONS: Despite some limits, our findings support the notion that deep learning methods can be used to simplify the diagnostic process and improve disease management.
Humans Artificial Intelligence Deep Learning X-Rays SARS-CoV-2 Public Health
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CheXclusion: Fairness gaps in deep chest X-ray classifiers.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2021
Machine learning systems have received much attention recently for their ability to achieve expert-level performance on clinical tasks, particularly in medical imaging. Here, we examine the extent to which state-of-the-art deep learning classifiers t...
Humans Computational Biology X-Rays Neural Networks, Computer Machine Learning
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Classifying Pneumonia among Chest X-Rays Using Transfer Learning.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Chest radiography has become the modality of choice for diagnosing pneumonia. However, analyzing chest X-ray images may be tedious, time-consuming and requiring expert knowledge that might not be available in less-developed regions. therefore, comput...
Pneumonia Radiography X-Rays Humans Diagnosis, Computer-Assisted Deep Learning
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3-To-1 Pipeline: Restructuring Transfer Learning Pipelines for Medical Imaging Classification via Optimized GAN Synthetic Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
The difficulty of applying deep learning algorithms to biomedical imaging systems arises from a lack of training images. An existing workaround to the lack of medical training images involves pre-training deep learning models on ImageNet, a non-medic...
Deep Learning Magnetic Resonance Imaging Algorithms Radiography Humans X-Rays
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Generating X-ray Images from Point Clouds Using Conditional Generative Adversarial Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Simulating medical images such as X-rays is of key interest to reduce radiation in non-diagnostic visualization scenarios. Past state of the art methods utilize ray tracing, which is reliant on 3D models. To our knowledge, no approach exists for case...
Neural Networks, Computer X-Rays
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Y-Net for Chest X-Ray Preprocessing: Simultaneous Classification of Geometry and Segmentation of Annotations.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Over the last decade, convolutional neural networks (CNNs) have emerged as the leading algorithms in image classification and segmentation. Recent publication of large medical imaging databases have accelerated their use in the biomedical arena. Whil...
Radiography X-Rays Machine Learning Algorithms Neural Networks, Computer
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