Publications by authors named "C Grau Salvat"

An image-quality CT phantom was scanned with three different 3D X-ray imaging guidance devices in the operating theatre: O-Arm, Loop-X, and Airo TruCT. Default acquisition and reconstruction parameters for lumbar spine procedures were used on each device. The tube current was set to a dose level of around 27 mGy.

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Rationale And Objectives: Interpreting radiographs in emergency settings is stressful and a burden for radiologists. The main objective was to assess the performance of three commercially available artificial intelligence (AI) algorithms for detecting acute peripheral fractures on radiographs in daily emergency practice.

Materials And Methods: Radiographs were collected from consecutive patients admitted for skeletal trauma at our emergency department over a period of 2 months.

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The interest of researchers, clinicians and radiologists, in artificial intelligence (AI) continues to grow. Deep learning is a subset of machine learning, in which the computer algorithm itself can determine the optimal imaging features to answer a clinical question. Convolutional neural networks are the most common architecture for performing deep learning on medical images.

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Objectives: A national retrospective survey on patient doses was performed by the French Society of Medical physicists to assess reference levels (RLs) in interventional radiology as required by the European Directive 2013/59/Euratom.

Methods: Fifteen interventional procedures in neuroradiology, vascular radiology and osteoarticular procedures were analysed. Kerma area product (KAP), fluoroscopy time (FT), reference air kerma and number of images were recorded for 10 to 30 patients per procedure.

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