Interpretation of ultrasonic deformation traces for making a diagnosis on local myocardial function has been known to be a challenging task in daily clinical practice. A traditional approach is to use values extracted at specific time points during the cardiac cycle which has the main drawback of not taking the temporal information of the deformation traces into account. This paper presents a framework for the automatic detection of ischemic myocardium by statistical analysis of the entire segmental strain and strain rate curves using principal component analysis (PCA). Having the PCA-derived parameters of the regional temporal profiles at hand, a spatio-temporal representation of the global left ventricle (LV) function is established to train a classification system. Experimental outcomes show that the proposed deformation representation of the LV can outperform its traditional counterpart in categorizing healthy from ischemic myocardium.
Titolo: | Automatic detection of ischemic myocardium by spatio-temporal analysis of echocardiographic strain and strain rate curves |
Autore/i: | TABASSIAN, MAHDI; ALESSANDRINI, MARTINO; Herbots, Lieven; Mirea, Oana; Engvall, Jan; DE MARCHI, LUCA; MASETTI, GUIDO; D'Hooge, Jan |
Autore/i Unibo: | |
Anno: | 2015 |
Titolo del libro: | 2015 IEEE International Ultrasonics Symposium, IUS 2015 |
Pagina iniziale: | 1 |
Pagina finale: | 4 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1109/ULTSYM.2015.0107 |
Abstract: | Interpretation of ultrasonic deformation traces for making a diagnosis on local myocardial function has been known to be a challenging task in daily clinical practice. A traditional approach is to use values extracted at specific time points during the cardiac cycle which has the main drawback of not taking the temporal information of the deformation traces into account. This paper presents a framework for the automatic detection of ischemic myocardium by statistical analysis of the entire segmental strain and strain rate curves using principal component analysis (PCA). Having the PCA-derived parameters of the regional temporal profiles at hand, a spatio-temporal representation of the global left ventricle (LV) function is established to train a classification system. Experimental outcomes show that the proposed deformation representation of the LV can outperform its traditional counterpart in categorizing healthy from ischemic myocardium. |
Data stato definitivo: | 11-lug-2016 |
Appare nelle tipologie: | 4.01 Contributo in Atti di convegno |