Towards fully automated inner ear analysis with deep-learning-based joint segmentation and landmark detection framework

Abstract Automated analysis of the inner ear anatomy in radiological data instead of time-consuming manual assessment is a worthwhile goal that could facilitate preoperative planning and clinical research. We propose a framework encompassing joint semantic segmentation of the inner ear and anatomica...

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Bibliographic Details
Main Authors: Jannik Stebani, Martin Blaimer, Simon Zabler, Tilmann Neun, Daniël M. Pelt, Kristen Rak
Format: Article
Language:English
Published: Nature Portfolio 2023-11-01
Series:Scientific Reports
Online Access:https://doi.org/10.1038/s41598-023-45466-9