Convolutional neural network for automated tooth segmentation on intraoral scans.

BACKGROUND: Tooth segmentation on intraoral scanned (IOS) data is a prerequisite for clinical applications in digital workflows. Current state-of-the-art methods lack the robustness to handle variability in dental conditions. This study aims to propose and evaluate the performance of a convolutional neural network (CNN) model for automatic tooth segmentation on IOS images. METHODS: A dataset of 761 IOS images (380 upper jaws, 381 lower jaws) was acquired using an intraoral scanner. The inclusion criteria included a full set of permanent teeth, teeth with orthodontic brackets, and partially edentulous dentition. A multi-step 3D U-Net pipeline was designed for automated tooth segmentation on IOS images. The model's performance was assessed in terms of time and accuracy. Additionally, the model was deployed on an online cloud-based platform, where a separate subsample of 18 IOS images was used to test the clinical applicability of the model by comparing three modes of segmentation: automated artificial intelligence-driven (A-AI), refined (R-AI), and semi-automatic (SA) segmentation. RESULTS: The average time for automated segmentation was 31.7 ± 8.1 s per jaw. The CNN model achieved an Intersection over Union (IoU) score of 91%, with the full set of teeth achieving the highest performance and the partially edentulous group scoring the lowest. In terms of clinical applicability, SA took an average of 860.4 s per case, whereas R-AI showed a 2.6-fold decrease in time (328.5 s). Furthermore, R-AI offered higher performance and reliability compared to SA, regardless of the dentition group. CONCLUSIONS: The 3D U-Net pipeline was accurate, efficient, and consistent for automatic tooth segmentation on IOS images. The online cloud-based platform could serve as a viable alternative for IOS segmentation.

Morphological characteristics of coronoid process and revisiting definition of coronoid hyperplasia.

The aim of this study was to assess the morphological characteristics of the coronoid process (CP) and define coronoid hyperplasia (CH) using cadaveric mandibles of a Caucasian population. A sample of 151 adult dry cadaveric mandibles (302 CPs) was acquired. Three distances were measured, which included the width, height, and length of CP. The surface area measurements involved area A: above the width distance line; area B: between incisura mandibulae-Alveolar ridge line and width distance line; area C: between distance lines of width and height. Finally, angulations of the CP and gonial angles were identified. Both length and surface area A + B acted as hyperplastic indicators. Based on the selection criteria, a sample of 197 CPs was included. The hooked shape (59%) was most commonly observed. No significant difference existed between left and right sides (p > 0.05). The mean values of length and surface area A + B were 2.2 ± 0.3 cm and 3.3 ± 0.8 cm2, and any values above 2.7 cm (n = 5 CPs- 2.5%) and 5.0 cm2 (n = 9 CPs- 4.6%) were described as hyperplastic, respectively. The presented data could act as quantitative reference for differentiating between normal and hyperplastic conditions.

Opinion of Belgian Egg Farmers on Hen Welfare and Its Relationship with Housing Type.

As of 2012, the EU has banned the use of conventional cages (CC) for laying hens, causing a shift in housing systems. This study's aim was to gain insight into farmers' opinions on hen health and welfare in their current housing systems. A survey was sent to 218 Belgian egg farmers, of which 127 (58.3%) responded, with 84 still active as egg farmer. Hen welfare tended to be less important in choosing the housing system for farmers with cage than with non-cage systems. Respondents currently using cage systems were more satisfied with hen health than respondents with non-cage systems. Reported mortality increased with farm size and was higher in furnished cages than in floor housing. Feather pecking, cannibalism, smothering and mortality were perceived to be higher in current housing systems than in CC, but only by respondents who shifted to non-cage systems from previously having had CC. Health- and production-related parameters were scored to be more important for hen welfare as compared to behavior-related parameters. Those without CC in the past rated factors relating to natural behavior to be more important for welfare than those with CC. This difference in opinion based on farmer backgrounds should be taken into account in future research.