3D Tibia Reconstruction Using 2D Computed Tomography Images

Abstract

OBJECTIVE Skeletal stress fracture of the lower limbs remains a significant problem for the military. The objective of this study was to develop a subject-specific 3D reconstruction of the tibia using only a few CT images for the prediction of peak stresses and locations. METHODS Full bilateral tibial CT scans were recorded for 63 healthy college male participants. A 3D finite element (FE) model of the tibia for each subject was generated from standard CT cross-section data (i.e., 4%, 14%, 38%, and 66% of the tibial length) via a transformation matrix. The final reconstructed FE models were used to calculate peak stress and location on the tibia due to a simulated walking load (3,700 N), and compared to the raw models. RESULTS The density-weighted, spatially-normalized errors between the raw and reconstructed CT models were small. The mean percent difference between the raw and reconstructed models for peak stress (0.62%) and location (−0.88%) was negligible. CONCLUSIONS Subject-specific tibia models can provide even great insights into the mechanisms of stress fracture injury, which are common in military and athletic settings. Rapid development of 3D tibia models allows for the future work of determining peak stress-related injury correlates to stress fracture outcomes.

Deep Learning Model Based on You Only Look Once Algorithm for Detection and Visualization of Fracture Areas in Three-Dimensional Skeletal Images

“…In this study, we demonstrated the accurate visualization of fractured regions using deep learning and 3D reconstructed images for the fractured bone from CT images. In other words, the purpose of this study was to evaluate the performance of the YOLO v4-based fracture detection method, and to show the possibility of an intuitive diagnosis by combining 3D image reconstruction and fracture detection [ 32 ]. The possibility of finding the fractured region from the 2D/3D CT images can be decreased according to internal or external conditions.…”