Automatic matching of computed tomography and stereolithography data.


Journal

Computer methods and programs in biomedicine
ISSN: 1872-7565
Titre abrégé: Comput Methods Programs Biomed
Pays: Ireland
ID NLM: 8506513

Informations de publication

Date de publication:
Jul 2019
Historique:
received: 22 12 2018
revised: 10 03 2019
accepted: 02 04 2019
entrez: 21 5 2019
pubmed: 21 5 2019
medline: 18 12 2019
Statut: ppublish

Résumé

Computed tomography (CT) is one of the most frequently used medical imaging methods. An important application area of CT is dental implants, which require precise inspection and analysis of oral structures. Since CT provides a precise 3D model of the teeth, bones and nerves, it can be used as a surgical guide for dental implants. Along with CT, optical 3D images called stereolithography (STL) have also been widely used. STL images obtained from optical 3D images can be used to show the 3D surfaces of oral structures. Since CT data and STL data deploy different technologies to obtain dental information, we can obtain more accurate dental implants by combining the two datasets. Since the two datasets are acquired by using different sensors, the datasets need to be registered. An automatic matching algorithm is proposed for CT and STL image registration, which is based on depth maps and maximum intensity projection. Then, fine tuning was performed based on volume matching. When applied to real-world databases, the proposed method provided an average matching error of 2.7 mm for the upper jaw and 2.3 mm for the lower jaw with an average processing time of about 19 s. The proposed method performs accurate registration of CT and STL.

Sections du résumé

BACKGROUND AND OBJECTIVE OBJECTIVE
Computed tomography (CT) is one of the most frequently used medical imaging methods. An important application area of CT is dental implants, which require precise inspection and analysis of oral structures. Since CT provides a precise 3D model of the teeth, bones and nerves, it can be used as a surgical guide for dental implants. Along with CT, optical 3D images called stereolithography (STL) have also been widely used. STL images obtained from optical 3D images can be used to show the 3D surfaces of oral structures. Since CT data and STL data deploy different technologies to obtain dental information, we can obtain more accurate dental implants by combining the two datasets. Since the two datasets are acquired by using different sensors, the datasets need to be registered.
METHODS METHODS
An automatic matching algorithm is proposed for CT and STL image registration, which is based on depth maps and maximum intensity projection. Then, fine tuning was performed based on volume matching.
RESULTS RESULTS
When applied to real-world databases, the proposed method provided an average matching error of 2.7 mm for the upper jaw and 2.3 mm for the lower jaw with an average processing time of about 19 s.
CONCLUSIONS CONCLUSIONS
The proposed method performs accurate registration of CT and STL.

Identifiants

pubmed: 31104709
pii: S0169-2607(18)31867-4
doi: 10.1016/j.cmpb.2019.04.003
pii:
doi:

Types de publication

Comparative Study Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

215-222

Informations de copyright

Copyright © 2019 Elsevier B.V. All rights reserved.

Auteurs

S Woo (S)

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea. Electronic address: wsy91@yonsei.ac.kr.

S Lee (S)

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea. Electronic address: nica@yonsei.ac.kr.

J Chae (J)

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea. Electronic address: jungyeob@yonsei.ac.kr.

J Rim (J)

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea. Electronic address: jhrim90@yonsei.ac.kr.

J Lee (J)

Dio Implant, Seoul 182-4, South Korea. Electronic address: billlee@dio.co.kr.

J Seo (J)

Dio Implant, Seoul 182-4, South Korea. Electronic address: sjj@dio.co.kr.

C Lee (C)

School of Electrical and Electronic Engineering, Yonsei University, Seoul 120-749, South Korea. Electronic address: chulhee@yonsei.ac.kr.

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Classifications MeSH