The invention provides an orthopedic implantation
instrument design method based on a structure-material-tissue regeneration relationship, which comprises the following steps: S1, acquiring anatomical structure, bone characteristics and
mechanical property data of an implantation part of a patient, obtaining structure-material and tissue regeneration quantitative data in combination with an animal experiment, and constructing a
data set; s2, based on the
data set, establishing a quantitative mapping model among the structure, the material parameters, the biomechanical property and the tissue regeneration effect by using
deep learning, and improving the model precision through historical data training and
cross validation; and S3, decomposing functional requirements and design parameters by applying axiom design, generating a structure and material scheme which is matched with anatomical features and meets functional requirements through Z-shaped mapping and
deep learning reverse optimization, and obtaining a final design of the personalized
implant instrument after iterative
verification. The method is based on a
deep learning data driving model and an axiom design theory, it is ensured that design parameters achieve expected performance, and design accuracy and reliability are remarkably improved.