Virtual registration of comminuted bone fracture and preoperative assessment of reconstructed bone model using the Procrustes algorithm based on CT dataset

A research work was undergone in a virtual bone reduction process for reconstruction of the comminuted pelvic bone fracture using a CT scan dataset of patients. This includes segmentation, 3D model optimization and bone registration technique. The accuracy of the reconstructed bone model was validated using Finite Element Method. Analysed and applied various segmentation techniques to segregate the injured bone structure. The ICP (Iterative Closest Point), Procrustes algorithm and Canny edge detection algorithm were applied to understand the bone registration process for surgery in detail. The average RMS error, mean absolute distance, mean absolute deviation, and mean signed distance of the reconstructed bone model using proposed algorithms involving 10 patient datasets in a group were found to be 1.77, 1.48, 1.51 and -0.31 mm respectively. The calculated RMS error value proved minimal error in semi-automatic registration than other existing automatic registration techniques. Therefore, the proposed approach is suitable for virtual bone reduction for comminuted pelvic bone fracture. This method could also be implemented for various other bone fracture reconstruction requirements.