Implant identification includes obtaining a
machine learning (ML) model trained to select, based on properties of anatomical surfaces of
anatomy adjacent to subject
anatomy to be replaced,
anatomy implant models of physical implants for replacement of the subject anatomy, obtaining
imaging data of an anatomical region of a patient, the anatomical region comprising a subject anatomy and other anatomy adjacent to the subject anatomy, determining properties of
anatomical surface(s) of the other anatomy, the
anatomical surface(s) being at a respective interface(s) between the other anatomy and the subject anatomy, and applying the ML model, using the determined properties of the
anatomical surface(s), and obtaining a selected
implant model selected by the ML model as a specification of a physical
implant for potential surgical implantation at least partially within the patient as a replacement of the subject anatomy.