Paper Info
Title
Automatic segmentation of jaw tissues in CT using active appearance models and semi-automatic landmarking.
Abstract
Preoperative planning systems are commonly used for oral implant surgery. One of the objectives is to determine if the quantity and quality of bone is sufficient to sustain an implant while avoiding critical anatomic structures. We aim to automate the segmentation of jaw tissues on CT images: cortical bone, trabecular core and especially the mandibular canal containing the dental nerve. This nerve must be avoided during implant surgery to prevent lip numbness. Previous work in this field used thresholds or filters and needed manual initialization. An automated system based on the use of Active Appearance Models (AAMs) is proposed. Our contribution is a completely automated segmentation of tissues and a semi-automatic landmarking process necessary to create the AAM model. The AAM is trained using 215 images and tested with a leave-4-out scheme. Results obtained show an initialization error of 3.25% and a mean error of 1.63mm for the cortical bone, 2.90 mm for the trabecular core, 4.76 mm for the mandibular canal and 3.40 mm for the dental nerve.
Year
DOI
Venue
2006
10.1007/11866565_21
MICCAI
Keywords
Field
DocType
mean error,mandibular canal,automated segmentation,active appearance model,automated system,automatic segmentation,manual initialization,cortical bone,aam model,initialization error,trabecular core,dental nerve,jaw tissue,semi-automatic landmarking
Biomedical engineering,Point distribution model,Cortical bone,Anatomy,Computer science,Implant,Artificial intelligence,Oral implant,Computer vision,Segmentation,Active appearance model,Mandibular canal,Initialization
Conference
Volume
Issue
ISSN
9
Pt 1
0302-9743
ISBN
Citations 
PageRank 
3-540-44707-5
15
1.00
References 
Authors
5
4
Name
Order
Citations
PageRank
Sylvia Rueda1557.79
José Antonio Gil2233.89
Raphaël Pichery3151.00
Mariano Alcañiz428534.73