|Title:||Empirical Mode Decomposition and Monogenic Signal-Based Approach for Quantification of Myocardial Infarction From MR Images||Authors:||Tran, Thi Thao
Pham, Van Truong
Yang, Hui Wen
Wang, Yung Hung
Shyu, Kuo Kai
WEN-YIH ISAAC TSENG
Su, Mao Yuan Marine
Lo, Men Tzung
|Keywords:||Ensemble empirical mode decomposition | gray zone | infarct core | monogenic signal | myocardial infarction||Issue Date:||1-Mar-2019||Journal Volume:||23||Journal Issue:||2||Start page/Pages:||731||Source:||IEEE Journal of Biomedical and Health Informatics||Abstract:||
© 2018 IEEE. Quantification of myocardial infarction on late Gadolinium enhancement cardiovascular magnetic resonance (LGE-CMR) images into heterogeneous infarct periphery (or gray zone) and infarct core plays an important role in cardiac diagnosis, especially in identifying patients at high risk of cardiovascular mortality. However, quantification task is challenging due to noise corrupted in cardiac MR images, the contrast variation, and limited resolution of images. In this study, we propose a novel approach for automatic myocardial infarction quantification, termed DEMPOT, which consists of three key parts: Decomposition of image into intrinsic modes, monogenic phase performing on combined dominant modes, and multilevel Otsu thresholding on the phase. In particular, inspired by the Hilbert-Huang transform, we perform the multidimensional ensemble empirical mode decomposition and 2-D generalization of the Hilbert transform known as the Riesz transform on the MR image to obtain the monogenic phase that is robust to noise and contrast variation. Then, a two-stage algorithm using multilevel Otsu thresholding is accomplished on the monogenic phase to automatically quantify the myocardium into healthy, gray zone, and infarct core regions. Experiments on LGE-CMR images with myocardial infarction from 82 patients show the superior performance of the proposed approach in terms of reproducibility, robustness, and effectiveness.
|Appears in Collections:||醫療器材與醫學影像研究所|
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.