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Augmenting data with GANs to segment melanoma skin lesions

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Augmenting data with GANs to segment melanoma skin lesions

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dc.contributor.author Pollastri, Federico es_ES
dc.contributor.author Bolelli, Federico es_ES
dc.contributor.author Paredes Palacios, Roberto es_ES
dc.contributor.author Grana, Costantino es_ES
dc.date.accessioned 2021-06-18T03:33:41Z
dc.date.available 2021-06-18T03:33:41Z
dc.date.issued 2020-06 es_ES
dc.identifier.issn 1380-7501 es_ES
dc.identifier.uri http://hdl.handle.net/10251/168114
dc.description.abstract [EN] This paper presents a novel strategy that employs Generative Adversarial Networks (GANs) to augment data in the skin lesion segmentation task, which is a fundamental first step in the automated melanoma detection process. The proposed framework generates both skin lesion images and their segmentation masks, making the data augmentation process extremely straightforward. In order to thoroughly analyze how the quality and diversity of synthetic images impact the efficiency of the method, we remodel two different well known GANs: a Deep Convolutional GAN (DCGAN) and a Laplacian GAN (LAPGAN). Experimental results reveal that, by introducing such kind of synthetic data into the training process, the overall accuracy of a state-of-the-art Convolutional/Deconvolutional Neural Network for melanoma skin lesion segmentation is increased. es_ES
dc.language Inglés es_ES
dc.publisher Springer-Verlag es_ES
dc.relation.ispartof Multimedia Tools and Applications es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Deep learning es_ES
dc.subject Convolutional neural networks es_ES
dc.subject Adversarial learning es_ES
dc.subject Skin lesion segmentation es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title Augmenting data with GANs to segment melanoma skin lesions es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s11042-019-7717-y es_ES
dc.rights.accessRights Cerrado es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation Pollastri, F.; Bolelli, F.; Paredes Palacios, R.; Grana, C. (2020). Augmenting data with GANs to segment melanoma skin lesions. Multimedia Tools and Applications. 79(21-22):15575-15592. https://doi.org/10.1007/s11042-019-7717-y es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1007/s11042-019-7717-y es_ES
dc.description.upvformatpinicio 15575 es_ES
dc.description.upvformatpfin 15592 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 79 es_ES
dc.description.issue 21-22 es_ES
dc.relation.pasarela S\424152 es_ES
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