INTRODUCTION: Since 1915, various researchers have tried to make a 3-dimensional (3D) model of the complete face, with the dentition in the anatomically correct position. This was a difficult and time-consuming process. With the introduction of 3D digital imaging of the face and dental casts, researchers have regained interest in this topic. The purpose of this technical report is to present a feasibility study of the integration of a digital dental cast into a 3D facial picture. METHODS: For the integration, 3 digital data sets were constructed: a digital dental cast, a digital 3D photograph of the patient with the teeth visible, and a digital 3D photograph of the patient with the teeth in occlusion. By using a special iterated closest point algorithm, these 3 data sets were matched to place them in the correct anatomical position. RESULTS: After matching the 3 data sets, we obtained a 3D digital model with the dental cast visible through the transparent picture of the patient's face. When the distance between the matched data sets was calculated, an average distance of 0.35 mm (SD, 0.32 mm) was shown. This means that matching the data sets is acceptable. CONCLUSIONS: It seems technically possible to make a data set of a patient's face with the dentition positioned into this 3D picture. Future research needs to establish the value of this 3D fused data set of the face and the dentition in orthodontic diagnosis and treatment planning.
INTRODUCTION: Since 1915, various researchers have tried to make a 3-dimensional (3D) model of the complete face, with the dentition in the anatomically correct position. This was a difficult and time-consuming process. With the introduction of 3D digital imaging of the face and dental casts, researchers have regained interest in this topic. The purpose of this technical report is to present a feasibility study of the integration of a digital dental cast into a 3D facial picture. METHODS: For the integration, 3 digital data sets were constructed: a digital dental cast, a digital 3D photograph of the patient with the teeth visible, and a digital 3D photograph of the patient with the teeth in occlusion. By using a special iterated closest point algorithm, these 3 data sets were matched to place them in the correct anatomical position. RESULTS: After matching the 3 data sets, we obtained a 3D digital model with the dental cast visible through the transparent picture of the patient's face. When the distance between the matched data sets was calculated, an average distance of 0.35 mm (SD, 0.32 mm) was shown. This means that matching the data sets is acceptable. CONCLUSIONS: It seems technically possible to make a data set of a patient's face with the dentition positioned into this 3D picture. Future research needs to establish the value of this 3D fused data set of the face and the dentition in orthodontic diagnosis and treatment planning.
Authors: Lucia H C Cevidanes; Ana Emilia Figueiredo Oliveira; Dan Grauer; Martin Styner; William R Proffit Journal: Semin Orthod Date: 2011-03-01 Impact factor: 0.970
Authors: Olivier J C van Vlijmen; Frits A Rangel; Stefaan J Bergé; Ewald M Bronkhorst; Alfred G Becking; Anne Marie Kuijpers-Jagtman Journal: Clin Oral Investig Date: 2010-07-17 Impact factor: 3.573
Authors: Lucia H C Cevidanes; Scott Tucker; Martin Styner; Hyungmin Kim; Jonas Chapuis; Mauricio Reyes; William Proffit; Timothy Turvey; Michael Jaskolka Journal: Am J Orthod Dentofacial Orthop Date: 2010-09 Impact factor: 2.650