%L eprints2767
%X Cardiac Phase-resolved Blood-Oxygen-Level-Dependent (CP-BOLD) MRI has been recently demonstrated to detect an ongoing myocardial ischemia at rest, taking advantage of spatio-temporal patterns in myocardial signal intensities, which are modulated by the presence of disease. However, this approach does require significant post-processing to detect the disease and to this day only a few images of the acquisition are used coupled with fixed thresholds to establish biomarkers. We propose a threshold-free unsupervised approach, based on dictionary learning and one-class support vector machines, which can generate a probabilistic ischemia likelihood map.
%A Marco Bevilacqua
%A Anirban Mukhopadhyay
%A Ilkay Oksuz
%A Cristian Rusu
%A Rohan Dharmakumar
%A Sotirios A. Tsaftaris
%T Dictionary-based Support Vector Machines for Unsupervised Ischemia Detection at Rest with CP-BOLD Cardiac MRI
%C Toronto, Ontario, Canada