Challenges and opportunities for extracting cardiovascular risk biomarkers from imaging data

I. A. Kakadiaris, E. G. Mendizabal-Ruiz, U. Kurkure, M. Naghavi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Complications attributed to cardiovascular diseases (CDV) are the leading cause of death worldwide. In the United States, sudden heart attack remains the number one cause of death and accounts for the majority of the $280 billion burden of cardiovascular diseases. In spite of the advancements in cardiovascular imaging techniques, the rate of deaths due to unpredicted heart attack remains high. Thus, novel computational tools are of critical need, in order to mine quantitative parameters from the imaging data for early detection of persons with a high likelihood of developing a heart attack in the near future (vulnerable patients). In this paper, we present our progress in the research of computational methods for the extraction of cardiovascular risk biomarkers from cardiovascular imaging data. In particular, we focus on the methods developed for the analysis of intravascular ultrasound (IVUS) data.

Original languageEnglish (US)
Title of host publicationProgress in Pattern Recognition, Image Analysis, Computer Vision and Applications - 14th Iberoamerican Conference on Pattern Recognition, CIARP 2009, Proceedings
Pages227-235
Number of pages9
DOIs
StatePublished - 2009
Event14th Iberoamerican Conference on Pattern Recognition, CIARP 2009 - Guadalajara, Jalisco, Mexico
Duration: Nov 15 2009Nov 18 2009

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5856 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference14th Iberoamerican Conference on Pattern Recognition, CIARP 2009
Country/TerritoryMexico
CityGuadalajara, Jalisco
Period11/15/0911/18/09

Keywords

  • Intravascular ultrasound
  • Vasa vasorum
  • Vulnerable patients

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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