In this paper we are presenting a method for achieving strain analysis of cardiac tissues from 3D ultrasound images. First of all, the left ventricle was segmented by an iterative snake algorithm which exploits the gradient vector flow field estimated from the 3D images. Once the ventricle was segmented, a set of points located on the external surface of the ventricle was selected. The movement of all these points along the entire cardiac cycle was calculated by using speckle tracking techniques based on the minimization of a Sum of Absolute Differences. The strain of all the segments connecting two of the considered points was computed, together with the rotation of the points along the long axis of the ventricle. The method was tested on images acquired from 10 patients: 3 with heart pathologies, 5 healthy subjects, and 2 patients with mild hypertrophy. The segmentation of the left ventricle with iterative methods demonstrated to be able to delineate the external surface of the ventricle in a consistent way. Preliminary results showed the feasibility of characterizing healthy subjects and patients with well-defined heart pathologies by using the outcomes achieved with the strain analysis.

Strain analysis of cardiac tissues from 3D ultrasound images through speckle tracking

LANCONELLI, NICO;MASETTI, SIMONE;
2013

Abstract

In this paper we are presenting a method for achieving strain analysis of cardiac tissues from 3D ultrasound images. First of all, the left ventricle was segmented by an iterative snake algorithm which exploits the gradient vector flow field estimated from the 3D images. Once the ventricle was segmented, a set of points located on the external surface of the ventricle was selected. The movement of all these points along the entire cardiac cycle was calculated by using speckle tracking techniques based on the minimization of a Sum of Absolute Differences. The strain of all the segments connecting two of the considered points was computed, together with the rotation of the points along the long axis of the ventricle. The method was tested on images acquired from 10 patients: 3 with heart pathologies, 5 healthy subjects, and 2 patients with mild hypertrophy. The segmentation of the left ventricle with iterative methods demonstrated to be able to delineate the external surface of the ventricle in a consistent way. Preliminary results showed the feasibility of characterizing healthy subjects and patients with well-defined heart pathologies by using the outcomes achieved with the strain analysis.
Image and Signal Processing and Analysis (ISPA), 2013 8th International Symposium on
477
482
Nico Lanconelli; Simone Masetti; Paola Nardinocchi; Luciano Teresi; Paolo Emilio Puddu; Concetta Torromeo; Vincenzo Giglio
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/219061
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