  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.
