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Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks

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Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks

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Del Amor, R.; Morales, S.; Colomer, A.; Mogensen, M.; Jensen, M.; Israelsen, NM.; Bang, O.... (2020). Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks. Frontiers in Medicine. 7:1-11. https://doi.org/10.3389/fmed.2020.00220

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/162954

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Title: Automatic Segmentation of Epidermis and Hair Follicles in Optical Coherence Tomography Images of Normal Skin by Convolutional Neural Networks
Author: del Amor, Rocío Morales, Sandra Colomer, Adrián Mogensen, Mette Jensen, Mikkel Israelsen, Niels M. Bang, Ole Naranjo Ornedo, Valeriana
UPV Unit: Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions
Issued date:
Abstract:
[EN] Optical coherence tomography (OCT) is a well-established bedside imaging modality that allows analysis of skin structures in a non-invasive way. Automated OCT analysis of skin layers is of great relevance to study ...[+]
Subjects: Skin OCT , Follicular structures , Layer segmentation , Epidermis , Convolutional neural networks , Pilosebaceous unit
Copyrigths: Reconocimiento (by)
Source:
Frontiers in Medicine. (eissn: 2296-858X )
DOI: 10.3389/fmed.2020.00220
Publisher:
Frontiers Media
Publisher version: https://doi.org/10.3389/fmed.2020.00220
Project ID:
info:eu-repo/grantAgreement/EC/H2020/732613/EU/Glaucoma – Advanced, LAbel-free High resolution Automated OCT Diagnostics/
Innovation Foundation Denmark/4107-00011A
AGENCIA ESTATAL DE INVESTIGACION/DPI2016-77869-C2-1-R
GENERALITAT VALENCIANA/PROMETEO/2019/109
Thanks:
This work has been partially supported by Horizon 2020, the European Union's Framework Programme for Research and Innovation, under grant agreement No. 732613 (GALAHAD Project), the Spanish Ministry of Economy and ...[+]
Type: Artículo

References

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