Cylindrical depth image based customized helical bone plate design.

3D printing Boolean operation Customized helical bone plate Cylindrical depth image Fracture fixation Implant design

Journal

Medical engineering & physics
ISSN: 1873-4030
Titre abrégé: Med Eng Phys
Pays: England
ID NLM: 9422753

Informations de publication

Date de publication:
Jul 2024
Historique:
received: 12 01 2024
revised: 06 05 2024
accepted: 20 05 2024
medline: 22 6 2024
pubmed: 22 6 2024
entrez: 21 6 2024
Statut: ppublish

Résumé

Commercial straight metal plates have been generally used to fix fractured bones, but recently, the need for customized and helical metal plates has emerged. Customized metal plates are designed to fit the shape of the fracture area that is a 3D curved surface, making it more difficult than designing on a 2D plane. Helical plates are researched due to their advantage in avoiding blood vessel damage compared to commercially available straight metal plates. In this paper, we propose a novel algorithm to design a customized helical metal plate for the femur using cylindrical depth images and Boolean operations. We also present the results of 3D printing a metal plate designed using the proposed algorithm, and the shape matching is verified by calculating the minimum distance between the surface of the printed plate and the surface of the femur.

Identifiants

pubmed: 38906577
pii: S1350-4533(24)00088-2
doi: 10.1016/j.medengphy.2024.104187
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

104187

Informations de copyright

Copyright © 2024 IPEM. Published by Elsevier Ltd. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest None declared.

Auteurs

Udeok Seo (U)

3D Convergence Technology Center, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea; School of Computer Science and Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea.

Yoo-Joo Choi (YJ)

Dept. of AI Software Engineering, Seoul Media Institute of Technology, Seoul, 03925, South Korea.

Ku-Jin Kim (KJ)

School of Computer Science and Engineering, Kyungpook National University, 80 Daehak-ro, Buk-gu, Daegu, 41566, South Korea. Electronic address: kujinkim@gmail.com.

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Classifications MeSH