Publications by authors named "Jean-Yves Airaud"

Purpose: The 2020 edition of these Data Challenges was organized by the French Society of Radiology (SFR), from September 28 to September 30, 2020. The goals were to propose innovative artificial intelligence solutions for the current relevant problems in radiology and to build a large database of multimodal medical images of ultrasound and computed tomography (CT) on these subjects from several French radiology centers.

Materials And Methods: This year the attempt was to create data challenge objectives in line with the clinical routine of radiologists, with less preprocessing of data and annotation, leaving a large part of the preprocessing task to the participating teams.

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Article Synopsis
  • The study aimed to create an algorithm using convolutional neural networks (CNN) that can automatically estimate coronary artery calcium (CAC) from unenhanced ECG-gated CT scans.
  • Researchers trained a CNN with a 3D U-Net architecture on 783 CT scans to detect and segment calcifications, calculating the Agatston score and comparing it to radiologist assessments.
  • The final model achieved a high accuracy (C-index of 0.951), although it struggled with small or low-density calcifications near the mitral valve, potentially enhancing workflow by automating the CAC scoring process.
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