Laura Fernandez-de-Manuel1, 2, Haiyan Ding, 13, Maria J. Ledesma Carbayo2, Elliot McVeigh1, Andres Santos2, Aravindan Kolandaivelu4, Daniel A. Herzka1
1Department of Biomedical Engineering, Johns Hopkins School of Medicine, Baltimore, MD, United States; 2Biomedical Image Technologies Lab., ETSI Telecomunicacion, Universidad Politecnica de Madrid and CIBER-BBN, Madrid, Spain; 3Department of Biomedical Engineering, Tsinghua University, Beijing, China; 4Department of Medicine, Cardiology, Johns Hopkins School of Medicine, Baltimore, MD, United States
Two-dimensional PSIR is a well established method of delineating scar in subjects with MI. Quantification of MI has been traditionally based on a threshold of more than 2 standard deviations (+2SD) above the mean of normal myocardial intensity. Newer alternative approaches with improved performance have yet to be applied to 3D PSIR imaging. In this work we compare different scar segmentation methods applied to a dataset of high-resolution 2D and 3D PSIR images from a swine model of MI. Proposed methods are based on Gaussian Mixture Model fitting and the Otsu algorithm, and are compared to the standard (+2SD).