Cardiovascular informatics

I. A. Kakadiaris; U. Kurkure; A. Bandekar; S. O’Malley; M. Naghavi

doi:10.1007/978-0-387-09749-7_19

Cardiovascular informatics

I. A. Kakadiaris, U. Kurkure, A. Bandekar, S. O’Malley, M. Naghavi

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

As cardiac imaging technology advances, large amounts of imaging data are being produced which are not being mined sufficiently by current diagnostic tools for early detection and diagnosis of cardiovascular disease.We aim to develop a computational framework to mine cardiac imaging data and provide quantitative measures for developing a new risk assessment method. In this chapter, we present novel methods to quantify pericardial fat in non-contrast cardiac computed tomography images automatically, and to detect and quantify neovascularization in the coronary vessels using intra-vascular ultrasound imaging.

Original language	English (US)
Title of host publication	Handbook of Biomedical Imaging
Subtitle of host publication	Methodologies and Clinical Research
Publisher	Springer US
Pages	363-374
Number of pages	12
ISBN (Electronic)	9780387097497
ISBN (Print)	9780387097480
DOIs	https://doi.org/10.1007/978-0-387-09749-7_19
State	Published - Jan 1 2015

ASJC Scopus subject areas

General Computer Science
General Medicine
General Biochemistry, Genetics and Molecular Biology

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10.1007/978-0-387-09749-7_19

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AU - Kurkure, U.

AU - Bandekar, A.

AU - O’Malley, S.

AU - Naghavi, M.

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Cardiovascular informatics

Abstract

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