Logo do repositório
 
Publicação

Light Field Image Dataset of Skin Lesions

2019-07Comunicação em conferência Acesso aberto
Ver registo simples
dc.contributor.authorFaria, Sérgio M. M.
dc.contributor.authorHenrique, Martinha
dc.contributor.authorFilipe, Jose N.
dc.contributor.authorPereira, Pedro M. M.
dc.contributor.authorTávora, Luís M. N.
dc.contributor.authorAssunção, Pedro A. A.
dc.contributor.authorSantos, Miguel O.
dc.contributor.authorFonseca-Pinto, Rui
dc.contributor.authorSantiago, Felicidade
dc.contributor.authorDominguez, Victoria
dc.date.accessioned2026-10-01T14:55:58Z
dc.date.available2026-10-01T14:55:58Z
dc.date.issued2019-07
dc.description.abstractLight field imaging technology has been attracting increasing interest because it enables capturing enriched visual information and expands the processing capabilities of traditional 2D imaging systems. Dense multiview, accurate depth maps and multiple focus planes are examples of different types of visual information enabled by light fields. This technology is also emerging in medical imaging research, like dermatology, allowing to find new features and improve classification algorithms, namely those based on machine learning approaches. This paper presents a contribution for the research community, in the form of a publicly available light field image dataset of skin lesions (named SKINL2 v1.0). This dataset contains 250 light fields, captured with a focused plenoptic camera and classified into eight clinical categories, according to the type of lesion. Each light field is comprised of 81 different views of the same lesion. The database also includes the dermatoscopic image of each lesion. A representative subset of 17 central view images of the light fields is further characterised in terms of spatial information (SI), colourfulness (CF) and compressibility. This dataset has high potential for advancing medical imaging research and development of new classification algorithms based on light fields, as well as in clinically-oriented dermatology studies.eng
dc.identifier.citationS. M. M. de Faria et al., "Light Field Image Dataset of Skin Lesions," 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), Berlin, Germany, 2019, pp. 3905-3908, doi: 10.1109/EMBC.2019.8856578.
dc.identifier.doi10.1109/embc.2019.8856578
dc.identifier.isbn978-1-5386-1311-5
dc.identifier.issn1558-4615
dc.identifier.urihttp://hdl.handle.net/10400.8/16942
dc.language.isoeng
dc.peerreviewedyes
dc.publisherIEEE
dc.relation.hasversionhttps://ieeexplore.ieee.org/document/8856578/
dc.relation.ispartof2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.subjectMedical dataset
dc.subjectSkin lesion
dc.subjectLight fields
dc.titleLight Field Image Dataset of Skin Lesionseng
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2019-07
oaire.citation.conferencePlaceBerlin, Germany
oaire.citation.endPage3908
oaire.citation.startPage3905
oaire.citation.title2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameFaria
person.familyNamede Oliveira Pegado de Noronha E Távora
person.familyNameAssunção
person.familyNameFonseca-Pinto
person.givenNameSergio
person.givenNameLuís Miguel
person.givenNamePedro
person.givenNameRui
person.identifier.ciencia-id8815-4101-28DD
person.identifier.ciencia-id121C-FADA-D750
person.identifier.ciencia-id6811-3984-C17B
person.identifier.ciencia-id681D-C547-B184
person.identifier.orcid0000-0002-0993-9124
person.identifier.orcid0000-0002-8580-1979
person.identifier.orcid0000-0001-9539-8311
person.identifier.orcid0000-0001-6774-5363
person.identifier.ridC-5245-2011
person.identifier.ridA-4827-2017
person.identifier.ridK-9449-2014
person.identifier.scopus-author-id14027853900
person.identifier.scopus-author-id6701838347
person.identifier.scopus-author-id26039086400
relation.isAuthorOfPublicationf69bd4d6-a6ef-4d20-8148-575478909661
relation.isAuthorOfPublication71940f24-f333-4ab6-abf6-00c7119a07c2
relation.isAuthorOfPublication25649bb9-f135-48e8-8d0f-3706b86701d3
relation.isAuthorOfPublication7eb9d123-1800-4afd-a2f6-91043353011b
relation.isAuthorOfPublication.latestForDiscoveryf69bd4d6-a6ef-4d20-8148-575478909661

Ficheiros

Principais
A mostrar 1 - 1 de 1
Miniatura
Nome:
170.pdf
Tamanho:
3.17 MB
Formato:
Adobe Portable Document Format
Ver/Abrir
Licença
A mostrar 1 - 1 de 1
Miniatura indisponível
Nome:
license.txt
Tamanho:
1.32 KB
Formato:
Item-specific license agreed upon to submission
Descrição:
Ver/Abrir

Coleções

ESTG - Comunicações em conferências e congressos internacionais