title: Automatic gender determination from 3D digital maxillary tooth plaster models based on the random forest algorithm and discrete cosine transform.
abstract: OBJECTIVE
  One of the first stages in the identification of an individual is gender determination. Through gender determination, the search spectrum can be reduced. In disasters such as accidents or fires, which can render identification somewhat difficult, durable teeth are an important source for identification. This study proposes a smart system that can automatically determine gender using 3D digital maxillary tooth plaster models.
  
  
  METHODS
  The study group was composed of 40 Turkish individuals (20 female, 20 male) between the ages of 21 and 24. Using the iterative closest point (ICP) algorithm, tooth models were aligned, and after the segmentation process, models were transformed into depth images. The local discrete cosine transform (DCT) was used in the process of feature extraction, and the random forest (RF) algorithm was used for the process of classification.
  
  
  RESULTS
  Classification was performed using 30 different seeds for random generator values and 10-fold cross-validation. A value of 85.166% was obtained for average classification accuracy (CA) and a value of 91.75% for the area under the ROC curve (AUC).
  
  
  CONCLUSIONS
  A multi-disciplinary study is performed here that includes computer sciences, medicine and dentistry. A smart system is proposed for the determination of gender from 3D digital models of maxillary tooth plaster models. This study has the capacity to extend the field of gender determination from teeth.
authors.affiliation: Department of Computer Engineering, Faculty of Engineering, Selçuk University, Aleaddin Keykubad Campus, Konya 42075, Turkey. Electronic address: betulakkoc@selcuk.edu.tr.
authors.forename: Betül
authors.initials: B
authors.lastname: Akkoç
authors.affiliation: Department of Computer Engineering, Konya Food & Agriculture University, Konya, Turkey. Electronic address: ahmet.arslan@gidatarim.edu.tr.
authors.forename: Ahmet
authors.initials: A
authors.lastname: Arslan
authors.affiliation: Department of Orthodontics, Necmettin Erbakan University, Konya, Turkey. Electronic address: hkok@konya.edu.tr.
authors.forename: Hatice
authors.initials: H
authors.lastname: Kök
mesh_terms: D000328:Adult; D000465:Algorithms; D019540:Area Under Curve; D003198:Computer Simulation; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008297:Male; D008437:Maxilla / Q000000981:diagnostic imaging*; D003765:Models, Dental; D010363:Pattern Recognition, Automated; D012372:ROC Curve; D015203:Reproducibility of Results; D012732:Sex Determination Analysis / Q000379:methods*; D012737:Sex Factors; D014057:Tomography, X-Ray Computed / Q000379:methods*; D014070:Tooth / Q000000981:diagnostic imaging*; D014421:Turkey; D055815:Young Adult
keywords: Feature extraction; Gender determination; Image processing; Random forest algorithm