Control parameter for polygonal simplification applied to medical images

The description of mechanical behavior of hard tissues by means of discrete models goes through various stages of analysis, which range from digital image processing and the specification of physical properties of tissue to the discrete model. Nowadays, technologies for acquiring medical images allow obtaining high resolution images. Obtaining the geometrical domain of these images requires high levels of hardware to process and store them, and polygonal simplification, with a defined minimum error, is one of the ways to compress the geometrical domain. Polygonal simplification is important in order to have the necessary and sufficient information to reconstruct surfaces and volumes that geometrically describe tissues and organs of the human body for their analysis by means of finite elements. In this paper an experimental control parameter is defined for polygon simplification. Experimental results proved that is possible to obtain a tridimensional model with an average volume variation of 87.49%, using only 36.3% of initial data, with a maximum error of 1.0% between initial and final polygon areas. All this process takes less processing time