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Sensors (Basel, Switzerland)2023; 23(21); 8940; doi: 10.3390/s23218940

Three-Dimensional Segmentation Assisted with Clustering Analysis for Surface and Volume Measurements of Equine Incisor in Multidetector Computed Tomography Data Sets.

Abstract: Dental diagnostic imaging has progressed towards the use of advanced technologies such as 3D image processing. Since multidetector computed tomography (CT) is widely available in equine clinics, CT-based anatomical 3D models, segmentations, and measurements have become clinically applicable. This study aimed to use a 3D segmentation of CT images and volumetric measurements to investigate differences in the surface area and volume of equine incisors. The 3D Slicer was used to segment single incisors of 50 horses' heads and to extract volumetric features. Axial vertical symmetry, but not horizontal, of the incisors was evidenced. The surface area and volume differed significantly between temporary and permanent incisors, allowing for easy eruption-related clustering of the CT-based 3D images with an accuracy of >0.75. The volumetric features differed partially between center, intermediate, and corner incisors, allowing for moderate location-related clustering with an accuracy of >0.69. The volumetric features of mandibular incisors' equine odontoclastic tooth resorption and hypercementosis (EOTRH) degrees were more than those for maxillary incisors; thus, the accuracy of EOTRH degree-related clustering was >0.72 for the mandibula and >0.33 for the maxilla. The CT-based 3D images of equine incisors can be successfully segmented using the routinely achieved multidetector CT data sets and the proposed data-processing approaches.
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Publication Date: 2023-11-02 PubMed ID: 37960639PubMed Central: PMC10650163DOI: 10.3390/s23218940Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

This study investigates the differences in the surface area and volume of horses’ teeth using 3D images obtained from a commonly used CT scanning method. With the help of software, the researchers made and analyzed 3D models of each individual tooth from 50 horses to determine variations in size and volume relating to tooth growth, position in the mouth, and a specific type of dental disease.

Methods and Analysis

  • The study focused on advanced dental diagnostic imaging technology, specifically multidetector computed tomography (CT).
  • The team used CT scans to create 3D models and to segment and measure distinct parts of equine or horse incisors (front teeth).
  • A software called 3D Slicer was used to segment the teeth and extract volumetric features.
  • The team analyzed whether any axial (horizontal or vertical) symmetry was present in the incisors.

Findings

  • Results indicated a vertical symmetry of the horse incisors, but not horizontal.
  • Significant differences were observed in the surface area and volume between temporary (baby teeth) and permanent incisors in horses.
  • These differences allowed for the eruption-related cluster analysis of the 3D images with a high degree of accuracy (over 75%).
  • There were also slight differences in the volumetric features between incisors at the center, between the center and the corner (intermediate), and at the corners of the horse mouth.
  • These differences led to a moderate level of location-related cluster accuracy (over 69%).

Dental Disease Comparison

  • The team compared the volumetric features of diseased mandibular (lower jaw) incisors afflicted with equine odontoclastic tooth resorption and hypercementosis (EOTRH) to those of maxillary (upper jaw) incisors.
  • The mandibular incisors affected by EOTRH showed greater volumetric features than the maxillary incisors.
  • As a result, the accuracy of EOTRH degree-related clustering was higher for the mandibular (over 72%) as compared to the maxillary (over 33%).

Conclusion

  • By using commonly obtained multidetector CT data sets, the study successfully segmented CT-based 3D images of equine incisors.
  • The proposed data-processing approaches have valuable clinical applications in identifying and assessing dental disease in horses.

Cite This Article

APA
Borowska M, Jasiński T, Gierasimiuk S, Pauk J, Turek B, Górski K, Domino M. (2023). Three-Dimensional Segmentation Assisted with Clustering Analysis for Surface and Volume Measurements of Equine Incisor in Multidetector Computed Tomography Data Sets. Sensors (Basel), 23(21), 8940. https://doi.org/10.3390/s23218940

Publication

Sensors (Basel, Switzerland)
ISSN: 1424-8220
NlmUniqueID: 101204366
Country: Switzerland
Language: English
Volume: 23
Issue: 21
PII: 8940

Researcher Affiliations

Borowska, Marta
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.
Jasiński, Tomasz
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Gierasimiuk, Sylwia
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.
Pauk, Jolanta
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.
Turek, Bernard
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Górski, Kamil
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Domino, Małgorzata
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.

MeSH Terms

  • Horses
  • Animals
  • Incisor / diagnostic imaging
  • Multidetector Computed Tomography
  • Tooth Resorption / veterinary
  • Hypercementosis / veterinary
  • Cluster Analysis
  • Maxilla

Grant Funding

  • Miniatura 6 No 2022/06/X/ST6/00431 / National Science Center
  • WI/WM-IIB/2/2021 / Polish Ministry of Science and Higher Education

Conflict of Interest Statement

The authors declare no conflict of interest.

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Citations

This article has been cited 1 times.
  1. Turek B, Pawlikowski M, Jankowski K, Borowska M, Skierbiszewska K, Jasiński T, Domino M. Selection of density standard and X-ray tube settings for computed digital absorptiometry in horses using the k-means clustering algorithm. BMC Vet Res 2025 Mar 13;21(1):165.
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