Automated CT bone segmentation using statistical shape modelling and local template matching
Details
Serval ID
serval:BIB_BD511AEF405D
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Automated CT bone segmentation using statistical shape modelling and local template matching
Journal
Computer methods in biomechanics and biomedical engineering
ISSN
1476-8259 (Electronic)
ISSN-L
1025-5842
Publication state
Published
Issued date
12/2019
Peer-reviewed
Oui
Volume
22
Number
16
Pages
1303-1310
Language
english
Notes
Publication types: Journal Article
Publication Status: ppublish
Publication Status: ppublish
Abstract
Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomical correspondences. The method was evaluated on demanding regions: normal and osteoarthritic scapulae, healthy and atrophied mandibles, and orbital bones. On average, results were accurate with surface distances of approximately 0.5 mm and average Dice coefficients >90%. Since anatomical correspondences are propagated during the segmentation process, this approach can directly yield anatomical measurements, provide design parameters for personalized surgical instruments, or determine the bone geometry to manufacture patient-specific implants.
Keywords
Algorithms, Automation, Bone and Bones/diagnostic imaging, Humans, Image Processing, Computer-Assisted, Mandible/diagnostic imaging, Models, Theoretical, Statistics as Topic, Tomography, X-Ray Computed, Bone segmentation, computed tomography, correction, statistical shape model, template matching
Pubmed
Web of science
Create date
13/09/2019 16:48
Last modification date
15/07/2020 5:26