Authors:
Olga Ferrer
1
;
Vinicius Duval
2
;
Jaime Delgado
3
;
Claudio Rolim
2
and
Ruben Tous
3
Affiliations:
1
University of La Laguna, UNESCO, Spain
;
2
University do Rio Grande do Sul, Brazil
;
3
Universitat Politecnica de Catalunya (UPC-BARCELONATECH), Spain
Keyword(s):
Optical Biopsy, Query by image, ISO-15938-12, MPEG Query Format, MPQF, ISO 24800-3, JPSearch, JPEG Query Format, JPQF, Artificial Intelligence, Multimedia standard.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Biomedical Engineering
;
Business Analytics
;
Cloud Computing
;
Data Engineering
;
Data Mining
;
Databases and Information Systems Integration
;
Datamining
;
e-Health
;
Enterprise Information Systems
;
Health Information Systems
;
Platforms and Applications
;
Semantic Interoperability
;
Sensor Networks
;
Signal Processing
;
Soft Computing
;
Support for Clinical Decision-Making
;
Telemedicine
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 mor-phology 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 i
mage 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.
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