Training and validation of a deep learning U-net architecture general model for automated segmentation of inner ear from CT
Jonathan Lim,
Aurore Abily,
Douraïed Ben Salem
et al.
Abstract:Background
The intricate three-dimensional anatomy of the inner ear presents significant challenges in diagnostic procedures and critical surgical interventions. Recent advancements in deep learning (DL), particularly convolutional neural networks (CNN), have shown promise for segmenting specific structures in medical imaging. This study aimed to train and externally validate an open-source U-net DL general model for automated segmentation of the inner ear from computed tomography (CT) scans, u… Show more
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