Classification of Hyperkinetic, Hypokinetic and Normal Segments in Ventriculographic Images, using Centerline Method

  • Hernando José Velandia-Villamizar M. Sc. Ingeniería Biomédica Universidad de Pamplona
  • Rubén de Jesús Medina-Molina Ph. D. Procesamiento de Señales y Comunicaciones Universidad de los Andes
  • Luis Enrique Mendoza M. Sc. Ingeniería Biomédica Universidad de Pamplona
Keywords: left ventricular wall, software platform, ventriculographic images, hypokinesis, hyperkinesis

Abstract

Evaluation  of  regional  left  ventricular  wall motion  is  of  vital  importance  at  the  clinical  level,  since  this  cavity  is  the  most  susceptible  to  severe  damage in diseases such as arterial hypertension,  diabetes mellitus  and  atherosclerosis.  This paper reports on the design of a software platform for the estimation of parameters describing the left ventricular wall motion in ventriculographic images. The system focuses on end-diastolic and  end-systolic  contours.  Firstly is  carried  out  a process of manual segmentation by the specialist, then 100 chords generated between two ventricular contours are  quantified,  which  allows  the  classification  of  these segments  (normal,  hyperkinetic  and  hypokinetic).  At last, the testing process is performed using actual data acquired in the Institute Autonomy Hospital Universitary of University of the Andes IAHULA.

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Published
2016-04-04
How to Cite
Velandia-Villamizar, H., Medina-Molina, R., & Mendoza, L. (2016). Classification of Hyperkinetic, Hypokinetic and Normal Segments in Ventriculographic Images, using Centerline Method. ITECKNE, 13(1), 57-63. https://doi.org/https://doi.org/10.15332/iteckne.v13i1.1382
Section
Research and Innovation Articles