title: Soft tissue coverage on the segmentation accuracy of the 3D surface-rendered model from cone-beam CT.
abstract: OBJECTIVE
  The aim of this study is to investigate the effect of soft tissue presence on the segmentation accuracy of the 3D hard tissue models from cone-beam computed tomography (CBCT).
  
  
  METHODS
  Seven pairs of CBCT Digital Imaging and Communication in Medicine (DICOM) datasets, containing data of human cadaver heads and their respective dry skulls, were used. The effect of the soft tissue presence on the accuracy of the segmented models was evaluated by performing linear and angular measurements and by superimposition and color mapping of the surface discrepancies after splitting the mandible and maxillo-facial complex in the midsagittal plane.
  
  
  RESULTS
  The linear and angular measurements showed significant differences for the more posterior transversal measurements on the mandible (p < 0.01). By splitting and superimposing the maxillo-facial complex, the mean root-mean-square error (RMSE) as a measurement of inaccuracy decreased insignificantly from 0.936 to 0.922 mm (p > 0.05). The RMSE value for the mandible, however, significantly decreased from 1.240 to 0.981 mm after splitting (p < 0.01).
  
  
  CONCLUSIONS
  The soft tissue presence seems to affect the accuracy of the 3D hard tissue model obtained from a cone-beam CT, below a generally accepted level of clinical significance of 1 mm. However, this level of accuracy may not meet the requirement for applications where high precision is paramount.
  
  
  CONCLUSIONS
  Accuracy of CBCT-based 3D surface-rendered models, especially of the hard tissues, are crucial in several dental and medical applications, such as implant planning and virtual surgical planning on patients undergoing orthognathic and navigational surgeries. When used in applications where high precision is paramount, the effect of soft tissue presence should be taken into consideration during the segmentation process.
authors.affiliation: Department of Orthodontics, University of Groningen, University Medical Centre Groningen, Hanzeplein 1, UMCG, 9700 RB, Groningen, The Netherlands.
authors.forename: J K
authors.initials: JK
authors.lastname: Dusseldorp
authors.affiliation: Department of Orthodontics, University of Groningen, University Medical Centre Groningen, Hanzeplein 1, UMCG, 9700 RB, Groningen, The Netherlands.
authors.forename: H C
authors.initials: HC
authors.lastname: Stamatakis
authors.affiliation: Department of Orthodontics, University of Groningen, University Medical Centre Groningen, Hanzeplein 1, UMCG, 9700 RB, Groningen, The Netherlands. y.ren@umcg.nl.
authors.forename: Y
authors.initials: Y
authors.lastname: Ren
mesh_terms: D059925:Anatomic Landmarks; D002102:Cadaver; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006257:Head / Q000000981:diagnostic imaging*; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D012016:Reference Values; D012886:Skull / Q000000981:diagnostic imaging
keywords: Accuracy; Cone-beam computed tomography; Segmentation; Soft tissues; Surface models