Deep learning-driven automated mitochondrial segmentation for analysis of complex transmission electron microscopy images

Abstract Mitochondria are central to cellular energy production and regulation, with their morphology tightly linked to functional performance. Precise analysis of mitochondrial ultrastructure is crucial for understanding cellular bioenergetics and pathology. While transmission electron microscopy (...

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Auteurs principaux:	Chan Jang, Hojun Lee, Jaejun Yoo, Haejin Yoon
Format:	Artigo
Langue:	Inglês
Publié:	Nature Portfolio 2025-05-01
Collection:	Scientific Reports
Sujets:	Mitochondrial morphology Deep learning segmentation Transmission electron microscopy imaging Interactive segmentation Uncertainty analysis Automated quantification
Accès en ligne:	https://doi.org/10.1038/s41598-025-03311-1
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