Training and validation of a deep learning U-net architecture general model for automated segmentation of inner ear from CT

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 sp...

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Библиографические подробности

Главные авторы:	Jonathan Lim, Aurore Abily, Douraïed Ben Salem, Loïc Gaillandre, Arnaud Attye, Julien Ognard
Формат:	Artigo
Язык:	Inglês
Опубликовано:	SpringerOpen 2024-09-01
Серии:	European Radiology Experimental
Предметы:	Artificial intelligence Ear (inner) Image processing (computer-assisted) Neural networks (computer) Tomography (x-ray computed)
Online-ссылка:	https://doi.org/10.1186/s41747-024-00508-3
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