Liver cancer is estimated to be the fifth most common in the world, while it is also considered the third leading cause of cancer death. In cases of primary liver cancer, surgery in combination with chemotherapy and radiotherapy can lead to a complete cure or significantly increase the patient’s life expectancy. Since the liver is an organ that performs several critical functions in the human body, the precise estimation of the disease (position and size of tumors and its vicinity to vessels) plays a vital role in a successful operation. In some cases, the removal of the tumor may be successful, but the percentage of the hepatic remnant may not be sufficient to sustain life. Therefore, accurate imaging of the tumor of the liver and proper planning of a difficult surgery to remove tumor(s) from a patient’s liver can be a lifesaver and lead to a complete cure of the disease. The aim of the present study is the initial accurate representation of the liver (parenchyma, tumors, vessels) as a digital three-dimensional (3D) model using advanced image processing and machine learning techniques and its 3D printing in 1:1 scale representing the full size of the liver with the tumor(s). A model of this type has been used at our University surgical department to plan complex hepatobiliary surgeries, provide more accurate information to the patients an