title: Development and evaluation of an automatic tumor segmentation tool: a comparison between automatic, semi-automatic and manual segmentation of mandibular odontogenic cysts and tumors.
abstract: BACKGROUND
  In the treatment of cancer in the head and neck region, computer-assisted surgery can be used to estimate location and extent by segmentation of the tumor. This article presents a new tool (Smartbrush), which allows for faster automated segmentation of the tumor.
  
  
  METHODS
  This new method was compared with other well-known techniques of segmentation. Thirty-eight patients with keratocystic odontogenic tumors were included in this study. The tumors were segmented using manual segmentation, threshold-based segmentation and segmentation using Smartbrush. All three methods were compared concerning usability, time expenditure and accuracy.
  
  
  RESULTS
  The results suggest that segmentation using Smartbrush is significantly faster with comparable accuracy.
  
  
  CONCLUSIONS
  After a period of adjustment to the program, one can comfortably get reliable results that, compared with other methods, are not as dependent on the user's experience. Smartbrush segmentation is a reliable and fast method of segmentation in tumor surgery.
authors.affiliation: Department of Craniomaxillofacial Surgery, Hannover Medical School, Hannover, Germany. Electronic address: rana.majeed@mh-hannover.de.
authors.forename: Majeed
authors.initials: M
authors.lastname: Rana
authors.affiliation: Brainlab AG, Feldkirchen, Germany.
authors.forename: Daniel
authors.initials: D
authors.lastname: Modrow
authors.affiliation: Brainlab AG, Feldkirchen, Germany.
authors.forename: Jens
authors.initials: J
authors.lastname: Keuchel
authors.affiliation: Department of Craniomaxillofacial Surgery, Hannover Medical School, Hannover, Germany.
authors.forename: Christopher
authors.initials: C
authors.lastname: Chui
authors.affiliation: Department of Differential Psychology and Psychological Assessment, Hamburg, Germany.
authors.forename: Madiha
authors.initials: M
authors.lastname: Rana
authors.affiliation: Department of Craniomaxillofacial Surgery, Hannover Medical School, Hannover, Germany.
authors.forename: Maximilian
authors.initials: M
authors.lastname: Wagner
authors.affiliation: Department of Craniomaxillofacial Surgery, Hannover Medical School, Hannover, Germany.
authors.forename: Nils-Claudius
authors.initials: NC
authors.lastname: Gellrich
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D021621:Imaging, Three-Dimensional / Q000379:methods / Q000706:statistics & numerical data; D008279:Magnetic Resonance Imaging / Q000379:methods / Q000706:statistics & numerical data; D008336:Mandibular Diseases / Q000601:surgery*; D009807:Odontogenic Cysts / Q000601:surgery*; D009808:Odontogenic Tumors / Q000601:surgery*; D015203:Reproducibility of Results; D025321:Surgery, Computer-Assisted / Q000379:methods* / Q000706:statistics & numerical data; D013997:Time Factors; D014057:Tomography, X-Ray Computed / Q000379:methods / Q000706:statistics & numerical data
keywords: Brainlab; Computer-assisted surgery; Segmentation; Tumor surgery