The project focuses on solutions that will improve the usability of holographic imaging in healthcare. The project consists both of development of solutions and clinical testing of their application in treatment and clinical decision-making. The HoloCare Cloud project aims at cloud-based automatic 3D modelling using machine learning, to transform medical images into holograms for use during surgical planning and navigation. This technology will be tested and validated in two different areas of specialized surgery: repair of congenital heart defects and tissue-saving surgery for liver tumors. The aim is automatic segmentation (making 3D models) from ordinary CT, MRI and ultrasound datasets. These are processed into holograms that provide real 3D as opposed to flat 2D screens. The first phase of the project was to establish a safe and reliable cloud solution. The second phase is to collect and analyze a sufficient number of image data to train algorithms for automatic image segmentation. The third phase of the project is clinical testing and research on the applications. This involves validation of the holographic tools, studying their impact on diagnostics and treatment and how they affect medical decision making..