Tumours can metastasize to the membrane covering the organs in the abdominal cavity. This is called peritoneal cancer and presents as numerous tumour nodules. Scoring the extensiveness and follow-up after therapy by the surgeon is subjective. Scoring is done with the peritoneal cancer index that divides the abdominal cavity into 13 regions and scores each region's extensiveness from 0-3. Thus, a patient can have a maximum score of 39. The aim of this research is to make the scoring objective with artificial intelligence (computer vision analysis). Therefore, algorithms are tested to recognize regions in the abdominal cavity. For this purpose, a large number of manually annotated images are provided. When this is performant, the algorithms are then fed with regions provided with annotated cancer nodules. The aim of the study is to assist the surgeon in objectively assessing the extensiveness of peritoneal cancer and the impact of treatments.