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Please use this identifier to cite or link to this item: http://dspace.ucuenca.edu.ec/handle/123456789/29217
Title: WebMedSA: A web-based framework for segmenting and annotating medical images using biomedical ontologies
Authors: Vega, F
Espinoza Mejía, Jorge Mauricio
La Cruz Puente Alexandra
Pérez Rocano, Wilson Rodrigo
Saquicela Galarza, Víctor Hugo
Solano Quinde, Lizandro Damian
Tello Guerrero, Marco Andrés
metadata.dc.ucuenca.correspondencia: La Cruz, A.; Electrical, Electronic and Telecommunication Department, Universidad de CuencaEcuador; email: alexandra.lacruz@ucuenca.edu.ec
metadata.dc.ucuenca.nombrerevista: 11th International Symposium on Medical Information Processing and Analysis SIPAIM 2015
Keywords: Dicom Ontology
Semantic Annotations
Volumetric Image
Web 3d-Visualizer
Issue Date: 17-Nov-2015
metadata.dc.ucuenca.embargoend: 1-Jan-2022
metadata.dc.ucuenca.volumen: 9681
metadata.dc.source: Proceedings of SPIE - The International Society for Optical Engineering
metadata.dc.identifier.doi: 10.1117/12.2214324
Publisher: SPIE
metadata.dc.type: Article
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.
URI: https://www.scopus.com/inward/record.uri?eid=2-s2.0-84958214034&doi=10.1117%2f12.2214324&partnerID=40&md5=53078f06004accaeb636658a88fa1d31
ISBN: 9781628419160
ISSN: 0277786X
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