AIMC Topic: Radiography

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Advanced Deep Learning Techniques Applied to Automated Femoral Neck Fracture Detection and Classification.

Journal of digital imaging Oct 1, 2020
To use deep learning with advanced data augmentation to accurately diagnose and classify femoral neck fractures. A retrospective study of patients with femoral neck fractures was performed. One thousand sixty-three AP hip radiographs were obtained fr...
Humans Deep Learning Radiography Femoral Neck Fractures Neural Networks, Computer Retrospective Studies
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Artificial Intelligence and Machine Learning in Radiology: Current State and Considerations for Routine Clinical Implementation.

Investigative radiology Sep 1, 2020
Although artificial intelligence (AI) has been a focus of medical research for decades, in the last decade, the field of radiology has seen tremendous innovation and also public focus due to development and application of machine-learning techniques ...
Radiology Workflow Humans Machine Learning Image Processing, Computer-Assisted Radiography
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Ethical considerations for artificial intelligence: an overview of the current radiology landscape.

Diagnostic and interventional radiology (Ankara, Turkey) Sep 1, 2020
Artificial intelligence (AI) has great potential to accelerate scientific discovery in medicine and to transform healthcare. In radiology, AI is about to enter into clinical practice and has a wide range of applications covering the whole diagnostic ...
Humans Artificial Intelligence Workflow Radiography Radiology
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A review on the use of artificial intelligence for medical imaging of the lungs of patients with coronavirus disease 2019.

Diagnostic and interventional radiology (Ankara, Turkey) Sep 1, 2020
The results of research on the use of artificial intelligence (AI) for medical imaging of the lungs of patients with coronavirus disease 2019 (COVID-19) has been published in various forms. In this study, we reviewed the AI for diagnostic imaging of ...
Humans Artificial Intelligence Pneumonia, Viral Image Interpretation, Computer-Assisted Betacoronavirus SARS-CoV-2 Sensitivity and Specificity Pandemics Radiography Tomography, X-Ray Computed COVID-19 Lung Coronavirus Infections Reproducibility of Results
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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...
Humans Pneumonia Diagnosis, Computer-Assisted Radiography Deep Learning X-Rays
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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...
Radiography X-Rays Deep Learning Magnetic Resonance Imaging Humans Algorithms
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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...
Neural Networks, Computer Machine Learning X-Rays Algorithms Radiography
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Learning Decision Ensemble using a Graph Neural Network for Comorbidity Aware Chest Radiograph Screening.

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 radiographs are primarily employed for the screening of cardio, thoracic and pulmonary conditions. Machine learning based automated solutions are being developed to reduce the burden of routine screening on Radiologists, allowing them to focus ...
Machine Learning Research Radiography Comorbidity Neural Networks, Computer
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A Systematic Search over Deep Convolutional Neural Network Architectures for Screening Chest Radiographs.

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 radiographs are primarily employed for the screening of pulmonary and cardio-/thoracic conditions. Being undertaken at primary healthcare centers, they require the presence of an on-premise reporting Radiologist, which is a challenge in low and...
Lung Radiography Research Neural Networks, Computer Reproducibility of Results
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Incremental inputs improve the automated detection of implant loosening using machine-learning algorithms.

The bone & joint journal Jun 1, 2020
AIMS: The aim of this study was to evaluate the ability of a machine-learning algorithm to diagnose prosthetic loosening from preoperative radiographs and to investigate the inputs that might improve its performance.
Aged Prosthesis Failure Algorithms Humans Middle Aged Radiography Male Female Machine Learning Knee Prosthesis Postoperative Complications
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