Overview
- Introduces a new algorithm for color images segmentation, based on a hexagonal grid, with very good results
- Covers a high number of experiments effectuated on a database with thousands of color medical images from digestive tract that are rarely used in medical annotation systems
- Annotation system uses an object-oriented model of the medical images database
Part of the book series: SpringerBriefs in Electrical and Computer Engineering (BRIEFSELECTRIC)
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Table of contents (7 chapters)
Keywords
About this book
In addition, the authors treat the problem of creating ontologies in an automatic way, starting from Medical Subject Headings (MESH). They have presented some efficient and relevant annotation models and also the basics of the annotation model used by the proposed system: Cross Media Relevance Models. Based on a text query the system will retrieve the images that contain objects described by the keywords.
Authors and Affiliations
Bibliographic Information
Book Title: Creating New Medical Ontologies for Image Annotation
Book Subtitle: A Case Study
Authors: Liana Stanescu, Dumitru Dan Burdescu, Marius Brezovan, Cristian Gabriel Mihai
Series Title: SpringerBriefs in Electrical and Computer Engineering
DOI: https://doi.org/10.1007/978-1-4614-1909-9
Publisher: Springer New York, NY
eBook Packages: Engineering, Engineering (R0)
Copyright Information: Springer Science+Business Media, LLC 2012
Softcover ISBN: 978-1-4614-1908-2Published: 15 December 2011
eBook ISBN: 978-1-4614-1909-9Published: 16 December 2011
Series ISSN: 2191-8112
Series E-ISSN: 2191-8120
Edition Number: 1
Number of Pages: VIII, 111
Number of Illustrations: 17 b/w illustrations, 10 illustrations in colour
Topics: Signal, Image and Speech Processing, Imaging / Radiology, Image Processing and Computer Vision, Algorithm Analysis and Problem Complexity