Automated CT bone segmentation using statistical shape modelling and local template matching

Détails

ID Serval
serval:BIB_BD511AEF405D
Type
Article: article d'un périodique ou d'un magazine.
Collection
Publications
Institution
Titre
Automated CT bone segmentation using statistical shape modelling and local template matching
Périodique
Computer methods in biomechanics and biomedical engineering
Auteur(s)
Taghizadeh E., Terrier A., Becce F., Farron A., Büchler P.
ISSN
1476-8259 (Electronic)
ISSN-L
1025-5842
Statut éditorial
Publié
Date de publication
12/2019
Peer-reviewed
Oui
Volume
22
Numéro
16
Pages
1303-1310
Langue
anglais
Notes
Publication types: Journal Article
Publication Status: ppublish
Résumé
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.
Mots-clé
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
Création de la notice
13/09/2019 16:48
Dernière modification de la notice
15/07/2020 5:26
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