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Retinal Image Synthesis for Glaucoma Assessment using DCGAN and VAE Models

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Retinal Image Synthesis for Glaucoma Assessment using DCGAN and VAE Models

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Díaz-Pinto, AY.; Colomer, A.; Naranjo Ornedo, V.; Morales, S.; Xu, Y.; Frangi, AF. (2019). Retinal Image Synthesis for Glaucoma Assessment using DCGAN and VAE Models. En Intelligent Data Engineering and Automated Learning – IDEAL 2018. Springer. 224-232. https://doi.org/10.1007/978-3-030-03493-1_24

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10251/124078

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Title: Retinal Image Synthesis for Glaucoma Assessment using DCGAN and VAE Models
Author:
Issued date:
Abstract:
The performance of a Glaucoma assessment system is highly affected by the number of labelled images used during the training stage. However, labelled images are often scarce or costly to obtain. In this paper, we address ...[+]
Subjects: Medical imaging , Retinal Image Synthesis , Fundus Images , DCGAN , VAE
Copyrigths: Embargado
ISBN: 978-3-030-03492-4
Source:
Intelligent Data Engineering and Automated Learning – IDEAL 2018.
DOI: 10.1007/978-3-030-03493-1_24
Publisher:
Springer
Publisher version: http://dx.doi.org/10.1007/978-3-030-03493-1_24
Conference name: International Conference on Intelligent Data Engineering and Automated Learning (IDEAL)
Conference place: Madrid, Spain
Conference date: Noviembre 21-23,2018
Series: Lecture Notes in Computer Science;11314
Project ID: info:eu-repo/grantAgreement/EC/H2020/732613/EU
Thanks:
We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan Xp GPU used for this research. This work was supported by the Project GALAHAD [H2020-ICT-2016-2017, 732613]
Type: Capítulo de libro Comunicación en congreso

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