D
2017
An investigation of key features of atherosclerotic plaques on B-images in comparison with histological patterns to ischemic stroke prediction
BLAHUTA, Jiří; Jakub SKÁCEL and Petr ČERMÁK
Basic information
Original name
An investigation of key features of atherosclerotic plaques on B-images in comparison with histological patterns to ischemic stroke prediction
Authors
BLAHUTA, Jiří (203 Czech Republic, guarantor, belonging to the institution); Jakub SKÁCEL (203 Czech Republic, belonging to the institution) and Petr ČERMÁK (203 Czech Republic, belonging to the institution)
Edition
New York, 2017 13TH INTERNATIONAL COMPUTER ENGINEERING CONFERENCE (ICENCO), p. 73-78, 6 pp. 2017
Other information
Type of outcome
Proceedings paper
Field of Study
10201 Computer sciences, information science, bioinformatics
Country of publisher
United States of America
Confidentiality degree
is not subject to a state or trade secret
Publication form
electronic version available online
RIV identification code
RIV/47813059:19240/17:A0000154
Organization
Filozoficko-přírodovědecká fakulta – Slezská univerzita v Opavě – Repository
Keywords in English
ultrasound; ischemic stroke; B-image; histological patterns; features image processing
Tags
International impact, Reviewed
Links
ED1.1.00/02.0070, research and development project.
V originále
This paper is focused on analysis of possible key features of atherosclerotic plaques displayed in B-images. There are two main aims: How to distinct normal and stenosis and how to compare stenosis in B-image in comparison with histological patterns. We have a set of B-images and corresponding histological patterns of atherosclerotic plaques which caused ischemic stroke. The goal of the paper is to investigate which features in B-images should be reliable and clear to distinct normal and stenosis and also which features could be compare with histological to determine ischemic stroke risk. There are some limitations in B-images such as complex structure and noise. Finding the reliable features is crucial step to create an expert system based on the analysis of these features. The output of the expert system should be set to probability of stenosis risk according to features of atherosclerotic plaque properties as rule base. The presented paper is a pilot study.
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