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WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies

Advances in medical imaging have fostered medical diagnosis based on digital images. Consequently, the number of studies by medical images diagnosis increases, thus, collaborative work and tele-radiology systems are required to effectively scale up to this diagnosis trend. We tackle the problem of t...

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Autor Principal: La Cruz Puente, Alexandra
Formato: Artículos
Lenguaje:eng
Publicado: 2016
Materias:
WEB-BASED
FRAMEWORK
SEGMENTING
ANNOTATING
Acceso en línea:http://repositorio.educacionsuperior.gob.ec/handle/28000/3164
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spelling oai:localhost:28000-31642017-04-13T16:23:39Z WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies La Cruz Puente, Alexandra WEB-BASED FRAMEWORK SEGMENTING ANNOTATING Advances in medical imaging have fostered medical diagnosis based on digital images. Consequently, the number of studies by medical images diagnosis increases, thus, collaborative work and tele-radiology systems are required to effectively scale up to this diagnosis trend. We tackle the problem of the collaborative access of medical images, and present WebMedSA, a framework to manage large datasets of medical images. WebMedSA relies on a PACS and supports the ontological annotation, as well as segmentation and visualization of the images based on their semantic description. Ontological annotations can be performed directly on the volumetric image or at different image planes (e.g., axial, coronal, or sagittal); furthermore, annotations can be complemented after applying a segmentation technique. WebMedSA is based on three main steps: (1) RDF-ization process for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML; (2) Integration of different biomedical ontologies (using L-MOM library), making this approach ontology independent; and (3) segmentation and visualization of annotated data which is further used to generate new annotations according to expert knowledge, and validation. Initial user evaluations suggest that WebMedSA facilitates the exchange of knowledge between radiologists, and provides the basis for collaborative work among them. http://spie.org/Publications/Proceedings/Paper/10.1117/12.2214324 2016-11-09T19:56:11Z 2016-11-09T19:56:11Z 2015 article Vega, Francisco. et al. (2015). WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies. Proceedings of SPIE - The International Society for Optical Engineering. 0277786X http://repositorio.educacionsuperior.gob.ec/handle/28000/3164 eng closedAccess
institution SENESCYT
collection Repositorio SENESCYT
biblioteca Biblioteca Senescyt
language eng
format Artículos
topic WEB-BASED
FRAMEWORK
SEGMENTING
ANNOTATING
spellingShingle WEB-BASED
FRAMEWORK
SEGMENTING
ANNOTATING
La Cruz Puente, Alexandra
WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
description Advances in medical imaging have fostered medical diagnosis based on digital images. Consequently, the number of studies by medical images diagnosis increases, thus, collaborative work and tele-radiology systems are required to effectively scale up to this diagnosis trend. We tackle the problem of the collaborative access of medical images, and present WebMedSA, a framework to manage large datasets of medical images. WebMedSA relies on a PACS and supports the ontological annotation, as well as segmentation and visualization of the images based on their semantic description. Ontological annotations can be performed directly on the volumetric image or at different image planes (e.g., axial, coronal, or sagittal); furthermore, annotations can be complemented after applying a segmentation technique. WebMedSA is based on three main steps: (1) RDF-ization process for extracting, anonymizing, and serializing metadata comprised in DICOM medical images into RDF/XML; (2) Integration of different biomedical ontologies (using L-MOM library), making this approach ontology independent; and (3) segmentation and visualization of annotated data which is further used to generate new annotations according to expert knowledge, and validation. Initial user evaluations suggest that WebMedSA facilitates the exchange of knowledge between radiologists, and provides the basis for collaborative work among them.
author La Cruz Puente, Alexandra
author_facet La Cruz Puente, Alexandra
author_sort La Cruz Puente, Alexandra
title WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
title_short WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
title_full WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
title_fullStr WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
title_full_unstemmed WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
title_sort webmedsa: a web-based framework for segmenting and annotating medical images using biomedical ontologies
publishDate 2016
url http://repositorio.educacionsuperior.gob.ec/handle/28000/3164
_version_ 1634995114076012544
score 11,871979

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