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Towards Automatic Glaucoma Assessment: An Encoder-decoder CNN for Retinal Layer Segmentation in Rodent OCT images

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Towards Automatic Glaucoma Assessment: An Encoder-decoder CNN for Retinal Layer Segmentation in Rodent OCT images

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Del Amor, R.; Morales, S.; Colomer, A.; Mossi García, JM.; Woldbye, D.; Klemp, K.; Larsen, M.... (2019). Towards Automatic Glaucoma Assessment: An Encoder-decoder CNN for Retinal Layer Segmentation in Rodent OCT images. En 2019 27th European Signal Processing Conference (EUSIPCO). IEEE. http://hdl.handle.net/10251/125893

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Title: Towards Automatic Glaucoma Assessment: An Encoder-decoder CNN for Retinal Layer Segmentation in Rodent OCT images
Author:
UPV Unit: Universitat Politècnica de València. Instituto Universitario de Telecomunicación y Aplicaciones Multimedia - Institut Universitari de Telecomunicacions i Aplicacions Multimèdia
Issued date:
Abstract:
[EN] Optical coherence tomography (OCT) is an important imaging modality that is used frequently to monitor the state of retinal layers both in humans and animals. Automated OCT analysis in rodents is an important method ...[+]
Subjects: Optical coherence tomography , Rodent OCT , Layer segmentation , Convolutional neural networks , Glaucoma assessment
Copyrigths: Reserva de todos los derechos
ISBN: 978-9-0827-9702-2
Source:
2019 27th European Signal Processing Conference (EUSIPCO). (issn: 2076-1465 )
Publisher:
IEEE
Conference name: European Signal Processing Conference (EUSIPCO) (formerly European Signal and Image Processing Conference)
Conference place: A Coruña, España
Conference date: Septiembre 02-07,2019
Project ID: info:eu-repo/grantAgreement/EC/H2020/732613/EU
Thanks:
This work was supported by the Project GALAHAD [H2020-ICT-2016-2017, 732613].
Type: Capítulo de libro Comunicación en congreso

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