A PSO Application in Skull Prosthesis Modelling by Superellipse

ELCVIA Electronic Letters on Computer Vision and Image Analysis

Marcelo Rudek¹  Thiago Greboge¹  Osiris Canciglieri Jr¹ 

[1]Industrial and Systems Engineering Post-Graduate Program - PPGEPSPontifical Catholic University of Parana - PUCPR

关键词: Image Modelling;    Image Analysis and Processing;    Applications;   

DOI  :  

学科分类：计算机科学（综合）

来源: ELCVIA

【 摘 要 】

This paper presents a method to create the geometric model of skull defects to be applied in anatomic prosthesis modelling. The approach is to generate an image that represents the missing information in the skull when bone`s defect is non-symmetric. We are proposing the use of superellipse concept to recover the parameters that represents the geometric shape of a skull bone curvature in tomography. If the superellipse is properly adjusted in each computed tomography slice, the arcs that represent the piece of missing bone can be modelled in 3D. The problem is that many similar ellipses can be created, and the best solution must be found. This research applies the Particle Swarm Optimization (PSO) algorithm in order to find the best solution for each tomographic slice. Once the solution found for each slice, the whole 3D missing information can be virtually rebuilt as an adjusted prosthesis model image.

【 授权许可】

Unknown