Towards the Semantic Representation of Biological Images

Author:

McLeod Kenneth1,Iskandar D. N. F. Awang2,Burger Albert1

Affiliation:

1. Department of Computer Science, Heriot-Watt University, Edinburgh, UK

2. Faculty of Computer Science & Information Technology, Universiti Malaysia Sarawak, Kota Samarahan, Malaysia

Abstract

Biomedical images and models contain vast amounts of information. Regrettably, much of this information is only accessible by domain experts. This paper describes a biological use case in which this situation occurs. Motivation is given for describing images, from this use case, semantically. Furthermore, links are provided to the medical domain, demonstrating the transferability of this work. Subsequently, it is shown that a semantic representation in which every pixel is featured is needlessly expensive. This motivates the discussion of more abstract renditions, which are dealt with next. As part of this, the paper discusses the suitability of existing technologies. In particular, Region Connection Calculus and one implementation of the W3C Geospatial Vocabulary are considered. It transpires that the abstract representations provide a basic description that enables the user to perform a subset of the desired queries. However, a more complex depiction is required for this use case.

Publisher

IGI Global

Subject

Decision Sciences (miscellaneous),Information Systems

Reference41 articles.

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3. Alam, A., Khan, L., & Thuraisingham, B. (2011). Geosptial resource description framework (GRDF) and security constructs. Journal of computer standards and interfaces (special issue: secure semantic web), 33(1), 35-41.

4. Allen Brain Atlas. (2012). Developmental mouse brain. Retrieved September 10, 2012, from http://developingmouse.brain-map.org

5. Andrews, S., & McLeod, K. (2011). Gene co-expression in mous embryo tissues. In F. Dau (Ed.), Proceedings of the 1st CUBIST workshop. 753. CEUR-WS.org.

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