Challenges and Opportunities for Extracting Cardiovascular Risk Biomarkers from Imaging Data

Authors:
I. A. Kakadiaris;E. G. Mendizabal-Ruiz;U. Kurkure;M. Naghavi
Affiliations:
Computational Biomedicine Lab, Departments of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering, University of Houston, Houston;Computational Biomedicine Lab, Departments of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering, University of Houston, Houston;Computational Biomedicine Lab, Departments of Computer Science, Electrical and Computer Engineering, and Biomedical Engineering, University of Houston, Houston;Society for Heart Attack Prevention and Eradication (SHAPE), Houston
Venue:
CIARP '09 Proceedings of the 14th Iberoamerican Conference on Pattern Recognition: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Year:
2009

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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.