Identification of toxoplasma gondii cysts in samples from Colombia using digital image processing

Zoonosis in Colombia is a subject of high epidemiological importance due to the transmission of pathogens to humans. T. gondii is an intracellular parasite (transmitted to human population) that causes various congenital diseases; including chorioretinitis, microcephaly, hydrocephaly, encephalomyelitis, mental retardation and hepatosplenomegaly, among others. The parasite affects also immunocompromissed patients that suffer from any type of cancer, organ transplantation and HIV. A deeper study on toxoplasmosis requires analysis of the developmental stages of the parasite, including the cyst stage, which allows it to evade the immune system and to get established in the host organism permanently. The goal of this work was to develop a digital image processing algorithm based on texture recognition to allow automatic detection of the cysts associated to pathogen T. gondii from isolated Colombian native strains in meat samples for human consumption, using computational software Matlab 2013, specifically through the Image Processing Toolbox. This algorithm allowed to segment the biological images, highlighting typical features of the cysts for calculate its eccentricity as a circularity criterion and finally to validate the efficiency of the algorithm.