A Novel Method Based on Interpolation for Accurate 3D Reconstruction from CT Images

Abstract

In intervention procedures or planning for joint replacement, the models developed must be precise and represent the natural look of the bones. For instance, the function of the knee joint is dependent on the motion of the femur. Therefore, precisely reconstructing the femur model assists in the design of the components for joint replacement. Moreover, when accurate measurements are taken for implant design, these models have a high effect on their accuracy. As a result, obtaining accurate 3D models of human bone tissue is important. Therefore, this paper proposes a novel method for accurate bone tissue reconstruction from CT data. The method is based on histogram modelling, interpolation, and reverse engineering techniques. Initially, soft tissues and unwanted artifacts are eliminated in order to extract the ROI (bone). After that, feature points are extracted based on pixel variance from each slice and then interpolated to create a 3D point cloud. Finally, a 3D model is created from point cloud data. Additionally, the model is printed using a 3D printer based on the FDM technique. Furthermore, the method is tested on CT stacks of femur and sheep bone in order to evaluate its strength and performance. Results indicated that the feature points collected by the proposed method could accurately describe the bone geometry. The error percentage between the proposed method and the actual bone was approximately 1.62%. The results indicate that the proposed method provides promising outcomes. Furthermore, the 3D model of bone is more compatible with the real bone.