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Linguistic Approach to Modeling of Coronary Arteries in Semantic Techniques of Image Retrieval | IEEE Conference Publication | IEEE Xplore

Linguistic Approach to Modeling of Coronary Arteries in Semantic Techniques of Image Retrieval

Publisher: IEEE

Abstract:

In recent years, medical images have become a constant part of our life. It is hard to imagine making a medical diagnosis without basic medical imaging apparatuses (CT, M...View more

Abstract:

In recent years, medical images have become a constant part of our life. It is hard to imagine making a medical diagnosis without basic medical imaging apparatuses (CT, MRI, USG, etc.). In order to fully utilize its potential, the image data must be stored in the proper way, particularly so that it is easily accessible. The latter is particularly important in a medical diagnostics - it is desired that a physician should have quick access to the comparative image data. In this context the authors present the possibility of using linguistic approach to modeling of coronary arteries in semantic techniques of image retrieval. The proposed methodology takes into account, among others, the basic topologies of arteries (balanced artery distribution, right dominant or left dominant) as well as individual sections or ramifications of these arteries. For the purpose of analysis and indexing these visualizations appropriate graph and sequential grammars are proposed.
Date of Conference: 08-10 November 2014
Date Added to IEEE Xplore: 29 January 2015
Electronic ISBN:978-1-4799-4171-1
Publisher: IEEE
Conference Location: Guangdong, China

I. Introduction

Coronary artery disease (CAD) also known as ischemic heart disease (IHD) is the most common type of heart disease. It is the leading cause of death in the developed countries in both men and women [1]. CAD happens when the arteries that supply blood to a heart muscle become hardened and narrowed. As a result, the heart muscle cannot get the blood or oxygen it needs and this can lead to a chest pain (angina pectoris) or a heart attack.

References

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