Positron Emission Tomography / Computed Tomography (PET/CT) and CT are an integral part of the diagnostic workup for various malignant solid tumor entities. Currently, response assessment for cancer treatment is performed manually by clinicians. Automation of tumour detection and segmentation may enable faster and more comprehensive information and data extraction. However, automated solutions for this task are lacking. Artificial Intelligence (AI)-based approaches may be an appropriate way to address lesion detection and segmentation in whole-body hybrid imaging (PET/CT and CT) to compensate workload and time pressure.