An integrated index for automated detection of infarcted myocardium from cross-sectional echocardiograms using texton-based features (Part 1)

Computers in Biology and Medicine
Vidya K SudarshanDhanjoo N Ghista

Abstract

Cross-sectional view echocardiography is an efficient non-invasive diagnostic tool for characterizing Myocardial Infarction (MI) and stages of expansion leading to heart failure. An automated computer-aided technique of cross-sectional echocardiography feature assessment can aid clinicians in early and more reliable detection of MI patients before subsequent catastrophic post-MI medical conditions. Therefore, this paper proposes a novel Myocardial Infarction Index (MII) to discriminate infarcted and normal myocardium using features extracted from apical cross-sectional views of echocardiograms. The cross-sectional view of normal and MI echocardiography images are represented as textons using Maximum Responses (MR8) filter banks. Fractal Dimension (FD), Higher-Order Statistics (HOS), Hu's moments, Gabor Transform features, Fuzzy Entropy (FEnt), Energy, Local binary Pattern (LBP), Renyi's Entropy (REnt), Shannon's Entropy (ShEnt), and Kapur's Entropy (KEnt) features are extracted from textons. These features are ranked using t-test and fuzzy Max-Relevancy and Min-Redundancy (mRMR) ranking methods. Then, combinations of highly ranked features are used in the formulation and development of an integrated MII. This calculated novel M...Continue Reading

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Citations

Nov 5, 2016·Nature Reviews. Cardiology·Gabriella CapturJames C Moon
Feb 11, 2020·Frontiers in Cardiovascular Medicine·Carlos Martin-IslaKarim Lekadir
May 14, 2021·Medical & Biological Engineering & Computing·Gelareh ValizadehAhmad Shalbaf

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