Linking image structures with medical ontology information

Authors:
Da Qi;Erika R. E. Denton;Reyer Zwiggelaar
Affiliations:
Department of Computer Science, University of Wales, Aberystwyth, UK;Norfolk and Norwich University Hospital, Norwich, UK;Department of Computer Science, University of Wales, Aberystwyth, UK
Venue:
IWDM'06 Proceedings of the 8th international conference on Digital Mammography
Year:
2006

Citing 6
Cited 3

Finite topology as applied to image analysis

Computer Vision, Graphics, and Image Processing
A review of recent texture segmentation and feature extraction techniques

CVGIP: Image Understanding
Incorporating Image Processing in a Clinical Decision Support System

IPMI '01 Proceedings of the 17th International Conference on Information Processing in Medical Imaging
On Ontology in Image Analysis

ISD '99 Selected Papers from the International Workshop on Integrated Spatial Databases, Digital Inages and GIS
Part and Complement: Fundamental Concepts in Spatial Relations

Annals of Mathematics and Artificial Intelligence
Ontology-mediated distributed decision support for breast cancer

AIME'05 Proceedings of the 10th conference on Artificial Intelligence in Medicine

An Ontology to Support Adaptive Training for Breast Radiologists

IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
The Evaluation of Effects on Breast Cancer Diagnoses When Using Mammographic Semantic Information

IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
Image analysis of histological features in molar pregnancies

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Medical ontologies are being developed with some of these specifically for mammographic computer aided diagnosis (CAD) systems. However, to provide full functionality for such mammographic CAD systems it is essential that the ontology information is fully linked to the image information. This linking can be through problem specific image attributes. However, such an approach tends to be non-generic. Here, we propose a framework that will use generic image structures and the topology that links the image structures. In the process we describe a comparison approach which takes the classes, attributes and semantics into account.