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Deep learning-based segmentation and density estimation of corneal nerves and dendritic cells from In Vivo confocal microscopy images

Abstract The purpose of this study was to compare manual assessment of corneal nerve fiber length (CNFL) and dendritic cell (DC) density with an automated assessment method utilizing deep learning segmentation to perform rule-based density estimation. Corneal images were acquired using in vivo confo...

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Gardado en:
Principais autores: Meichen Ji, Yan Song, Jenny Roth, Ava Dashti, Jorge Lazo, Alisa Lincke, António Filipe Teixeira Macedo, Welf Löwe, Neil Lagali
Formato: Artigo
Idioma:Inglês
Publicado: Nature Portfolio 2026-01-01
Series:Scientific Reports
Assuntos:
Deep learning
Confocal microscopy
Cornea
Nerve fibers
Dendritic cells
Segmentation
Acceso en liña:https://doi.org/10.1038/s41598-025-34412-6
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