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Automatic Classification of Nodules from 2D Ultrasound Images Using Deep Learning Networks.

Tewele W TarekeSarah LeclercCatherine VuilleminPerrine BuffierElodie CrevisyAmandine NguyenMarie-Paule Monnier MeteauPauline LegrisSerge AngioliniAlain Lalande
Published in: Journal of imaging (2024)
We propose a deep learning architecture that effectively classifies thyroid nodules as requiring FNA or not from ultrasound images. Despite challenges related to image variability, class imbalance, and interpretability, our method demonstrated a high classification accuracy with minimal false negatives, showing its potential to reduce unnecessary FNAs in clinical settings.
Keyphrases
  • deep learning
  • convolutional neural network
  • artificial intelligence
  • magnetic resonance imaging
  • machine learning
  • contrast enhanced ultrasound
  • ultrasound guided
  • optical coherence tomography