IVUS image processing and semantic analysis for cardiovascular diseases risk prediction

Charalampos Doulaverakis; Maria Papadogiorgaki; Vasileios Mezaris; Antonis Billis; Eirini Parissi; Ioannis Kompatsiaris; Anastasios Gounaris; Yiannis S. Chatzizisis; George D. Giannoglou

doi:10.1504/IJBET.2010.032700

IVUS image processing and semantic analysis for cardiovascular diseases risk prediction

Charalampos Doulaverakis, Maria Papadogiorgaki, Vasileios Mezaris, Antonis Billis, Eirini Parissi, Ioannis Kompatsiaris, Anastasios Gounaris, Yiannis S. Chatzizisis, George D. Giannoglou

Research output: Contribution to journal › Article › peer-review

6 Scopus citations

Abstract

The work presented in this paper is part of a system able to perform risk classification of patients based on medical image analysis and on the semantically structured information of patient data from medical records and biochemical data. More specifically, the paper focuses on Intravascular Ultrasound (IVUS) image processing and the automated segmentation developed to extract the useful arterial boundaries. This is coupled with the design and implementation of a semantic reasoning-enabled knowledge base in OWL that integrates data from heterogeneous sources and incorporates functionality for DL classification. Performance evaluation of both IVUS image processing and knowledge base is discussed.

Original language	English (US)
Pages (from-to)	349-374
Number of pages	26
Journal	International Journal of Biomedical Engineering and Technology
Volume	3
Issue number	3-4
DOIs	https://doi.org/10.1504/IJBET.2010.032700
State	Published - Apr 2010
Externally published	Yes

Keywords

IVUS image processing
OWL
RBF
Radial basis function
Risk prediction
SWRL
Semantic analysis

ASJC Scopus subject areas

Biomedical Engineering

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10.1504/IJBET.2010.032700

Cite this

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abstract = "The work presented in this paper is part of a system able to perform risk classification of patients based on medical image analysis and on the semantically structured information of patient data from medical records and biochemical data. More specifically, the paper focuses on Intravascular Ultrasound (IVUS) image processing and the automated segmentation developed to extract the useful arterial boundaries. This is coupled with the design and implementation of a semantic reasoning-enabled knowledge base in OWL that integrates data from heterogeneous sources and incorporates functionality for DL classification. Performance evaluation of both IVUS image processing and knowledge base is discussed.",

keywords = "IVUS image processing, OWL, RBF, Radial basis function, Risk prediction, SWRL, Semantic analysis",

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AU - Doulaverakis, Charalampos

AU - Papadogiorgaki, Maria

AU - Mezaris, Vasileios

AU - Billis, Antonis

AU - Parissi, Eirini

AU - Kompatsiaris, Ioannis

AU - Gounaris, Anastasios

AU - Chatzizisis, Yiannis S.

AU - Giannoglou, George D.

PY - 2010/4

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AB - The work presented in this paper is part of a system able to perform risk classification of patients based on medical image analysis and on the semantically structured information of patient data from medical records and biochemical data. More specifically, the paper focuses on Intravascular Ultrasound (IVUS) image processing and the automated segmentation developed to extract the useful arterial boundaries. This is coupled with the design and implementation of a semantic reasoning-enabled knowledge base in OWL that integrates data from heterogeneous sources and incorporates functionality for DL classification. Performance evaluation of both IVUS image processing and knowledge base is discussed.

KW - IVUS image processing

KW - OWL

KW - RBF

KW - Radial basis function

KW - Risk prediction

KW - SWRL

KW - Semantic analysis

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IVUS image processing and semantic analysis for cardiovascular diseases risk prediction

Abstract

Keywords

ASJC Scopus subject areas

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