Antoine Galibourg1,2, Jean Dumoncel1, Norbert Telmon1,3, Adèle Calvet1,4, Jérôme Michetti2, Delphine Maret1,2. 1. 1 Laboratoire Anthropologie Moléculaire et Imagerie de Synthèse, Université Paul Sabatier, Toulouse, France. 2. 2 Faculté de Chirurgie Dentaire, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France. 3. 3 Service de Médecine Légale, Hôpital de Rangueil, Toulouse, France. 4. 4 Faculté de médecine, Université Paul Sabatier, Centre Hospitalier Universitaire, Toulouse, France.
Abstract
OBJECTIVE: Tooth 3D automatic segmentation (AS) is being actively developed in research and clinical fields. Here, we assess the effect of automatic segmentation using a watershed-based method on the accuracy and reproducibility of 3D reconstructions in volumetric measurements by comparing it with a semi-automatic segmentation(SAS) method that has already been validated. METHODS: The study sample comprised 52 teeth, scanned with micro-CT (41 µm voxel size) and CBCT (76; 200 and 300 µm voxel size). Each tooth was segmented by AS based on a watershed method and by SAS. For all surface reconstructions, volumetric measurements were obtained and analysed statistically. Surfaces were then aligned using the SAS surfaces as the reference. The topography of the geometric discrepancies was displayed by using a colour map allowing the maximum differences to be located. RESULTS: AS reconstructions showed similar tooth volumes when compared with SAS for the 41 µm voxel size. A difference in volumes was observed, and increased with the voxel size for CBCT data. The maximum differences were mainly found at the cervical margins and incisal edges but the general form was preserved. CONCLUSION: Micro-CT, a modality used in dental research, provides data that can be segmented automatically, which is timesaving. AS with CBCT data enables the general form of the region of interest to be displayed. However, our AS method can still be used for metrically reliable measurements in the field of clinical dentistry if some manual refinements are applied.
OBJECTIVE:Tooth 3D automatic segmentation (AS) is being actively developed in research and clinical fields. Here, we assess the effect of automatic segmentation using a watershed-based method on the accuracy and reproducibility of 3D reconstructions in volumetric measurements by comparing it with a semi-automatic segmentation(SAS) method that has already been validated. METHODS: The study sample comprised 52 teeth, scanned with micro-CT (41 µm voxel size) and CBCT (76; 200 and 300 µm voxel size). Each tooth was segmented by AS based on a watershed method and by SAS. For all surface reconstructions, volumetric measurements were obtained and analysed statistically. Surfaces were then aligned using the SAS surfaces as the reference. The topography of the geometric discrepancies was displayed by using a colour map allowing the maximum differences to be located. RESULTS: AS reconstructions showed similar tooth volumes when compared with SAS for the 41 µm voxel size. A difference in volumes was observed, and increased with the voxel size for CBCT data. The maximum differences were mainly found at the cervical margins and incisal edges but the general form was preserved. CONCLUSION: Micro-CT, a modality used in dental research, provides data that can be segmented automatically, which is timesaving. AS with CBCT data enables the general form of the region of interest to be displayed. However, our AS method can still be used for metrically reliable measurements in the field of clinical dentistry if some manual refinements are applied.
Authors: D Maret; F Molinier; J Braga; O A Peters; N Telmon; J Treil; J M Inglèse; A Cossié; J L Kahn; M Sixou Journal: J Dent Res Date: 2010-10-07 Impact factor: 6.116
Authors: Satoshi Yamaguchi; Yasufumi Yamanishi; Lucas S Machado; Shuji Matsumoto; Nick Tovar; Paulo G Coelho; Van P Thompson; Satoshi Imazato Journal: J Prosthodont Res Date: 2017-04-17 Impact factor: 4.642
Authors: Marcus Stoetzer; Franziska Nickel; Majeed Rana; Juliana Lemound; Daniela Wenzel; Constantin von See; Nils-Claudius Gellrich Journal: Head Face Med Date: 2013-04-20 Impact factor: 2.151