Deep Learning Model for Automated Segmentation of Orbital Structures in MRI Images.
Journal:
Clinical neuroradiology
Published Date:
Jun 26, 2025
Abstract
BACKGROUND: Magnetic resonance imaging (MRI) is a crucial tool for visualizing orbital structures and detecting eye pathologies. However, manual segmentation of orbital anatomy is challenging due to the complexity and variability of the structures. Recent advancements in deep learning (DL), particularly convolutional neural networks (CNNs), offer promising solutions for automated segmentation in medical imaging. This study aimed to train and evaluate a U-Net-based model for the automated segmentation of key orbital structures.
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