Global feature for left ventricular dysfunction detection based on shape deformation tracking

Adhi Harmoko Saputro, Mohd. Marzuki Mustafa, Aini Hussain, Wan Mimi Diyana Wan Zaki, Oteh Maskon, Ika Faizura Mohd Nor

Research output: Contribution to journalArticle

Abstract

Left ventricular (LV) shape alteration is closely correlated with cardiac disease and LV function. In this paper, we propose a feature to detect LV dysfunction globally by analyzing the LV shape deformation in systolic contraction. The feature is an index that is extracted from geometric measurement of LV shape such as the length of the long axis, the short axis, and the apical diameter. A framework for computing the features is also proposed that consists of shape model construction and motion estimation of myocardial boundary. The LV shape model is extracted from apical 2 and 4 chamber views of 2D echocardiography. The long axis, the short axis, and the apical diameter were redefined according to the LV shape constructed. An optical flow technique was used to estimate the position of the LV boundary in each frame. The classification of the LV dysfunction was performed using linear discriminant analysis (LDA) and neural networks (NNs). The 2D echocardiography dataset collected from routine clinical check-up were used to validate the proposed method by comparing the computation result and cardiac expert diagnose. Classification performance and statistical analysis, which was performed to discriminate between healthy and diseased data, indicated promising results. The global LV features would provide a strong basis for a global LV function diagnosis and a global cardiac pathology assessment.

Original languageEnglish
Article number1550017
JournalBiomedical Engineering - Applications, Basis and Communications
Volume27
Issue number2
DOIs
Publication statusPublished - 25 Apr 2015

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Echocardiography
Left Ventricular Dysfunction
Left Ventricular Function
Optical flows
Discriminant Analysis
Discriminant analysis
Pathology
Motion estimation
Heart Diseases
Statistical methods
Neural networks
Datasets

Keywords

  • Echocardiography
  • Feature extraction
  • Left ventricular dysfunction
  • Shape tracking

ASJC Scopus subject areas

  • Biophysics
  • Biomedical Engineering
  • Bioengineering

Cite this

Global feature for left ventricular dysfunction detection based on shape deformation tracking. / Saputro, Adhi Harmoko; Mustafa, Mohd. Marzuki; Hussain, Aini; Wan Zaki, Wan Mimi Diyana; Maskon, Oteh; Mohd Nor, Ika Faizura.

In: Biomedical Engineering - Applications, Basis and Communications, Vol. 27, No. 2, 1550017, 25.04.2015.

Research output: Contribution to journalArticle

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