Background: Hepatobiliary parasites are often the cause of a granulomatous reaction, they are responsible of radiological confusion mimicking tumor lesions. In imaging radiology, this is characterized by the absence of lesional contrast, the presence of calcification and the presence of hepatic granulomas. The example of toxocariasis that is caused by the toxocaracani or Taticati parasite manifested in ultrasound and CT-scan (computerized tomography), by multiple small intrahepatic lesions, oval or elongated and poorly defined. This result is hypo or isoechogenic. Objectif: If the confirmation of the diagnosis passes by a liver biopsy on specific eosinophilic granulomas we propose in this study the identification of the granulomas of origin toxocarose and to differentiate them from the tumoral forms. Methods: Given the complexity of the system, the factors taken into account are the volume distribution of the density, the size, and the shape of the contour, the location and the living conditions of the patient. These variables are considered input variables to a fuzzy system. The output variable expresses the nature of the granuloma. As the fuzzy logic that is a subfield of artificial intelligence deals with the uncertain and imprecise, its application in this area proves adequate. A database is established from the real cases in the form (If... Then). Conclusion: Once the fuzzy algorithm is done, it allows identifying the nature of the tumoral granulomas or toxocariasis before biological techniques confirmation.

Hepatobiliary, Parasites, Toxocariasis, CT-Scan, Granulomas, Tumor, Fuzzy Logic