Automated recognition of the pericardium contour on processed CT images using genetic algorithms

O. Rodrigues, L. O. Rodrigues, L. S.N. Oliveira, A. Conci, P. Liatsis

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

This work proposes the use of Genetic Algorithms (GA) in tracing and recognizing the pericardium contour of the human heart using Computed Tomography (CT) images. We assume that each slice of the pericardium can be modelled by an ellipse, the parameters of which need to be optimally determined. An optimal ellipse would be one that closely follows the pericardium contour and, consequently, separates appropriately the epicardial and mediastinal fats of the human heart. Tracing and automatically identifying the pericardium contour aids in medical diagnosis. Usually, this process is done manually or not done at all due to the effort required. Besides, detecting the pericardium may improve previously proposed automated methodologies that separate the two types of fat associated to the human heart. Quantification of these fats provides important health risk marker information, as they are associated with the development of certain cardiovascular pathologies. Finally, we conclude that GA offers satisfiable solutions in a feasible amount of processing time.

Original languageBritish English
Pages (from-to)38-45
Number of pages8
JournalComputers in Biology and Medicine
Volume87
DOIs
StatePublished - 1 Aug 2017

Keywords

  • Adipose tissue
  • Computed tomography
  • Ellipse tracing
  • Epicardial
  • Epicardium
  • Genetic algorithm
  • Human heart
  • Image segmentation
  • Metaheuristic
  • Pericardium

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