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Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM)
dc.contributor.author | Ferrer-Roca, Olga |
dc.contributor.author | Duval, Vinicius |
dc.contributor.author | Delgado Mercè, Jaime |
dc.contributor.author | Rolim, Claudio |
dc.contributor.author | Tous Liesa, Rubén |
dc.contributor.other | Universitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors |
dc.date.accessioned | 2010-06-01T13:24:10Z |
dc.date.available | 2010-06-01T13:24:10Z |
dc.date.created | 2010 |
dc.date.issued | 2010 |
dc.identifier.citation | Ferrer-Roca, O. [et al.]. Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM). A: THE INTERNATIONAL CONFERENCE ON HEALTH INFORMATICS. "HEALTHINF 2010". HOTEL SIDI SALER, VALENCIA: 2010, p. 166-172. |
dc.identifier.isbn | 978-989-674-016-0 |
dc.identifier.uri | http://hdl.handle.net/2117/7467 |
dc.description.abstract | The use of Optical Biopsies-OB (in the present case Confocal endomicroscopy-CEM) is limited due to difficulties to interpret images. The OB-CEM are taken by endoscopists, not trained in microscopic morphology which is the domain of the surgical pathology. To gain diagnostic confidence the endoscopists could consult the images to a pathologist or could use the technique proposed in the paper. That is, to search for similar images on Internet to compare the diagnosis. The present paper is a positioning paper of how to build a CEM-image metadata to be used by the multimedia standards ISO-15938-12:2008 and ISO-24800-3 in order to search on line using a “query by image”. Metadata semantics based on Kudo colorectal crypt architecture was used for annotation or automatic image extraction. The training set was composed of 25 OB-CEM chromo-colonoscopy images taken with a FICE (Fujinon Intelligent Chromoendoscopy). Those parameters were, whenever possible, automatically extracted from the image and included in the metadata for image mining. Future developments will annotate histological images is such a way that the query could also retrieve the histological image. |
dc.format.extent | 7 p. |
dc.language.iso | eng |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Arquitectura de computadors |
dc.subject | Àrees temàtiques de la UPC::Ciències de la visió::Òptica física |
dc.subject | Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial |
dc.subject.lcsh | Artificial intelligence |
dc.subject.lcsh | Multimedia |
dc.title | Query by image medical training: optical biopsy with confocal endoscopy (OB-CEM) |
dc.type | Conference report |
dc.subject.lemac | Intel·ligència artificial |
dc.subject.lemac | Multimèdia -- Congressos |
dc.contributor.group | Universitat Politècnica de Catalunya. DMAG - Grup d'Aplicacions Multimèdia Distribuïdes |
dc.identifier.dl | 303438/09 |
dc.rights.access | Open Access |
local.identifier.drac | 2528211 |
dc.description.version | Postprint (published version) |
local.citation.author | Ferrer-Roca, O.; Duval, V.; Delgado, J.; Rolim, C.; Tous, R. |
local.citation.contributor | THE INTERNATIONAL CONFERENCE ON HEALTH INFORMATICS |
local.citation.pubplace | HOTEL SIDI SALER, VALENCIA |
local.citation.publicationName | HEALTHINF 2010 |
local.citation.startingPage | 166 |
local.citation.endingPage | 172 |