Due to an increasing number of additive manufactured parts, the need for automated part-inspection utilizing CT data is constantly growing. So far, available commercial solutions for data evaluation and defect detection in CT data do not fulfill the Airbus requirements for NDT inspection [1]. Therefore, all of today’s evaluations have to be done manually according to a qualified inspection process. As a consequence, the part inspection time is high and inspection costs contribute significantly to the overall costs of the additive manufactured parts. To overcome these limitations, Airbus Central R&T has been working on algorithmic methodologies to support inspectors in this costly and time consuming process.