In the last few years, the Artificial Intelligence (AI) has made big steps forward in many fields of telemedicine, especially in the process of biomedical images acquired by several technologies and techniques like Ultrasound, Computed Tomography (TC), Magnetic Risonance Imaging (MRI), etc.. In particular, the segmentation of biomedical images is very important to identify pathologies and lesions of organs allowing the doctor to intervene before any complications of the organ disease. This thesis project is developed at SynDiag srl, a company that develops artificial intelligence algorithms to support the interpretation of medical images, in particular ultrasound images of ovarian cysts. The goal is the automatic segmentation, through the implementation of Deep Neural Networks (DNN) like the U-net, of CT images concerning the liver, using the software library of Tensorflow 2.0.