An automatic reduction method of 3D bone fragments based on a novel section contour point descriptor

Author:

Zhang Song12,Wang Qifeng12,Cao Qiming12,Li Zhe3,Yang Liang4,Liu Bin12ORCID

Affiliation:

1. International School of Information Science & Engineering (DUT‐RUISE) Dalian University of Technology Dalian China

2. DUT‐RU Co‐Research Center of Advanced ICT for Active Life Dalian University of Technology Dalian China

3. School of Biomedical Engineering Sun Yat‐sen University Guangzhou China

4. The Second Hospital Dalian Medical University Dalian China

Abstract

AbstractComminuted fractures are orthopedic traumas with greater surgical difficulty. In clinical treatment, a great challenge is precise reduction of multiple broken bone fragments; Another great challenge is personalized and precise internal fixation after reduction. For these two issues, we designed an automated method framework for precise reduction and internal fixation of comminuted fractures. First, the Gaussian mixture model (GMM) is used to distinguish section points and noise points in a broken bone model; Second, ellipse fitting is carried out to achieve section points matching and a descriptor is proposed to describe the section features; Then, the Convolution Auto‐Encoder (CAE) and genetic algorithm are used to extract feature vectors; Finally, after broken bone models registration, internal fixed plate can be reconstructed. Three verification experiments for comminuted bone fracture show this method has high accuracy and good efficiency. It can provide support for minimally invasive treatment for comminuted fractures.

Funder

Fundamental Research Funds for the Central Universities

National Natural Science Foundation of China

Publisher

Wiley

Subject

Applied Mathematics,Computational Theory and Mathematics,Molecular Biology,Modeling and Simulation,Biomedical Engineering,Software

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