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Left Ventricular Systolic Dysfunction Identification by Motion Analysis

Authors: J, Manivannan; M, Ramasubba Reddy; S, Thanikachalam; R, Ajay Kumar;

Left Ventricular Systolic Dysfunction Identification by Motion Analysis

Abstract

This paper presents a new technique for identification of regional dysfunctions in the left ventricle from 2-D echocardiography. It uses a novel left ventricular border tracking algorithm based on Fuzzy inference system. In this paper we show how the regional dysfunction present in the left ventricle can be identified by tracking the movement of centre of mass of left ventricle in a 2D space. The path pattern of that point traced over the cardiac cycles shows variation between the two groups. The main advantage of this proposed approach is the smaller date handling in regional dysfunction identifications unlike other existing methods. The method is illustrated on the real 2D echocardiograph dataset that includes patients having dysfunctions in the left ventricular wall. The diagnostic potential of this method is explained in detail.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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