RDF-ization of DICOM Medical Images towards Linked Health Data Cloud

Tello, Andrés; Cruz, Alexandra La; Saquicela, Víctor; Espinoza, Mauricio; Vidal, María-Esther

doi:10.1007/978-3-319-13117-7_193

Cited by 5 publications

(2 citation statements)

References 9 publications

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“…For instance, there are technologies such as ontologies or the relation with databases following the principles of Linked Data. [13] and [14] revise and discuss the process of RDF metadata conversion and enrichment. This process aims to create, from metadata, a database structured in RDF, with the insertion of other related properties, to increase the enhancement of that dataset.…”

Section: Resultsmentioning

confidence: 99%

Digital Image Representation Model Enriched with Semantic Web Technologies: Visual and Non-Visual Information

Roa-Martínez,

Coneglian,

Vidotti

2023

Rev. Fac. Ing.

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The types of content of digital images, visual (syntactic and semantic) and non-visual, cause the complexity of their representation. Considering these contents separately hinders digital image retrieval because this creates a gap between the contents of the image and its representation. Therefore, this work aims to present a representation model of visual and non-visual information of digital images, with semantic enrichment through the Semantic Web technologies. For that, a qualitative methodology with a bibliographical approach was used. Theoretical subsidies of the topics addressed were sought, and it has an applied focus since it proposes a model and its exemplification. The developed model depicts the representation image process and allows the semantic enrichment of the data. This enrichment facilitates the retrieval in multiple contexts with technologies that favor the use of the data through inferences. Also, a use case with digital medical images is presented, demonstrating the feasibility of the proposal. It is concluded that the representation of visual and non-visual content aims to improve the way images are retrieved in digital information environments. The junction of the content and the context of images should be considered, even though search mechanisms usually treat this separately due to the disaggregation of image representation itself.

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Section: Resultsmentioning

confidence: 99%

Digital Image Representation Model Enriched with Semantic Web Technologies: Visual and Non-Visual Information

Roa-Martínez,

Coneglian,

Vidotti

2023

Rev. Fac. Ing.

View full text Add to dashboard Cite

show abstract

“…CBIR systems supported on a GRID platform have a broad reach and the processes involved can be distributed. Because images in our database are already annotated semantically using different ontologies, 25,26 and these ontological terms are included on a RDF/XML repositories, searching over the repository can be done using different terms from more important biomedical ontologies. 25, 26 Figure 5 presents the proposed architecture organized as a three-layered architecture using the gateway design.…”

Section: Proposed Architecturementioning

confidence: 99%