Preoperative virtual reduction method for pelvic fractures based on statistical shape models and partial surface data

Virtual reduction is crucial for successful and accurate reduction of pelvic fractures.Various methods have been proposed in this regard.However,not all of them are applicable to every pelvic fracture.Among these methods,the efficiency and accuracy of the method based on statistical shape models in clinical applications require further improvement.This study proposes a virtual reduction method for pelvic fractures that uses statistical shape models and partial surface data of a broken pelvis.Simulated fracture and clinical case experiments were conducted to validate the accuracy and effectiveness of the proposed method.The simulated fracture experiments yielded an average error of 1.57±0.39 mm and a maximum error of 12.82±3.54 mm.The virtual reduction procedure takes approximately 40 s.Based on three clinical case experiments,the proposed method achieves an acceptable level of accuracy compared with manual reduction by a surgeon.The proposed method offers the advantages of shorter virtual reduction times and satisfactory reduction accuracy.In the future,it will be integrated into the preoperative planning system for pelvic fracture reduction,thereby improving patient outcomes.

Accuracy optimization of virtual iterative reduction algorithm under time constraint

The factors like production accuracy and completion time are the determinants of the optimal scheduling of the complex products work-flow,so the main research direction of modern work-flow technology is how to assure the dynamic balance between the factors.Based on the work-flow technology,restraining the completion time,and analyzing the deficiency of traditional minimum critical path algorithm,a virtual iterative reduction algorithm(VIRA)was proposed,which can improve production accuracy effectively with time constrain.The VIRA with simplification as the core abstracts a virtual task that can predigest the process by combining the complex structures which are cyclic or parallel,finally,by using the virtual task and the other task in the process which is the iterative reduction strategy,determines a path which can make the production accuracy and completion time more balanced than the minimum critical path algorithm.The deadline,the number of tasks,and the number of cyclic structures were used as the factors affecting the performance of the algorithm,changing the influence factors can improve the performance of the algorithm effectively through the analysis of detailed data.Consequently,comparison experiments proved the feasibility of the VIRA.