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Home / Equine Research Bank / Biomedicines / Application of Two-Dimensional Entropy Measures to Detect th...
Biomedicines2022; 10(11); 2914; doi: 10.3390/biomedicines10112914

Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model.

Abstract: Dental disorders are a serious health problem in equine medicine, their early recognition benefits the long-term general health of the horse. Most of the initial signs of Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) syndrome concern the alveolar aspect of the teeth, thus, the need for early recognition radiographic imaging. This study is aimed to evaluate the applicability of entropy measures to quantify the radiological signs of tooth resorption and hypercementosis as well as to enhance radiographic image quality in order to facilitate the identification of the signs of EOTRH syndrome. A detailed examination of the oral cavity was performed in eighty horses. Each evaluated incisor tooth was assigned to one of four grade-related EOTRH groups (0-3). Radiographs of the incisor teeth were taken and digitally processed. For each radiograph, two-dimensional sample (SampEn2D), fuzzy (FuzzEn2D), permutation (PermEn2D), dispersion (DispEn2D), and distribution (DistEn2D) entropies were measured after image filtering was performed using Normalize, Median, and LaplacianSharpening filters. Moreover, the similarities between entropy measures and selected Gray-Level Co-occurrence Matrix (GLCM) texture features were investigated. Among the 15 returned measures, DistEn2D was EOTRH grade-related. Moreover, DistEn2D extracted after Normalize filtering was the most informative. The EOTRH grade-related similarity between DistEn2D and Difference Entropy (GLCM) confirms the higher irregularity and complexity of incisor teeth radiographs in advanced EOTRH syndrome, demonstrating the greatest sensitivity (0.50) and specificity (0.95) of EOTRH 3 group detection. An application of DistEn2D to Normalize filtered incisor teeth radiographs enables the identification of the radiological signs of advanced EOTRH with higher accuracy than the previously used entropy-related GLCM texture features.
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Publication Date: 2022-11-13 PubMed ID: 36428482PubMed Central: PMC9687516DOI: 10.3390/biomedicines10112914Google 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.

The study explores how using different types of entropy measures can improve x-ray imaging detection of tooth resorption and hypercementosis in horses. The findings show that using these methods may make radiographs more effective in diagnosing equine dental disorders.

Research Methodology

  • The researchers conducted an in-depth examination of the oral cavities of 80 horses. These examinations focused on the incisors, due to their relevance to Equine Odontoclastic Tooth Resorption and Hypercementosis (EOTRH) syndrome.
  • Each incisor tooth was classified into one of four grade-related EOTRH groups, ranging from 0 (least severe) to 3 (most severe).
  • X-rays were taken of each incisor tooth and the radiographs acquired were then digitally processed. This processing involved applying three different filters: Normalize, Median, and LaplacianSharpening.

Measuring Entropy

  • After filtering, the authors measured five different kinds of entropy on each radiograph: two-dimensional sample entropy (SampEn2D), fuzzy entropy (FuzzEn2D), permutation entropy (PermEn2D), dispersion entropy (DispEn2D), and distribution entropy (DistEn2D).
  • These entropy measures quantify the complexity and irregularity of the radiographic images, providing insight into the severity of tooth disorders.
  • The study also examined the correlation between these entropy measures and certain texture features of the radiographs captured by Gray-Level Co-occurrence Matrix (GLCM) methods.

Findings and Implications

  • Out of the 15 measures collected, DistEn2D was found to be the most related to the grade of EOTRH.
  • The DistEn2D measure extracted after applying the Normalize filter was particularly informative. It showed a strong similarity with GLCM’s Difference Entropy, which confirmed higher levels of irregularity and complexity in advanced cases of EOTRH.
  • The researchers concluded that using DistEn2D on Normalize filtered x-rays had higher sensitivity and specificity in detecting advanced stages of EOTRH, compared to the previous entropy-related GLCM texture features.
  • This suggests that applying these entropy techniques to radiographic images could improve the early detection of equine dental disorders, contributing to better health management of horses.

Cite This Article

APA
Górski K, Borowska M, Stefanik E, Polkowska I, Turek B, Bereznowski A, Domino M. (2022). Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model. Biomedicines, 10(11), 2914. https://doi.org/10.3390/biomedicines10112914

Publication

Biomedicines
ISSN: 2227-9059
NlmUniqueID: 101691304
Country: Switzerland
Language: English
Volume: 10
Issue: 11
PII: 2914

Researcher Affiliations

Górski, Kamil
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Borowska, Marta
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, 15-351 Bialystok, Poland.
Stefanik, Elżbieta
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Polkowska, Izabela
  • Department and Clinic of Animal Surgery, Faculty of Veterinary Medicine, University of Life Sciences, 20-950 Lublin, Poland.
Turek, Bernard
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.
Bereznowski, Andrzej
  • Division of Veterinary Epidemiology and Economics, Institute of Veterinary Medicine, Warsaw University of Life Sciences, Nowoursynowska 159c, 02-776 Warsaw, Poland.
Domino, Małgorzata
  • Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences, 02-787 Warsaw, Poland.

Conflict of Interest Statement

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Citations

This article has been cited 3 times.
  1. Górski K, Borowska M, Turek B, Pawlikowski M, Jankowski K, Bereznowski A, Polkowska I, Domino M. An application of the density standard and scaled-pixel-counting protocol to assess the radiodensity of equine incisor teeth affected by resorption and hypercementosis: preliminary advancement in dental radiography. BMC Vet Res 2023 Aug 9;19(1):116.
    doi: 10.1186/s12917-023-03675-4pubmed: 37559089google scholar: lookup
  2. Górski K, Borowska M, Stefanik E, Polkowska I, Turek B, Bereznowski A, Domino M. Correction: Górski et al. Application of Two-Dimensional Entropy Measures to Detect the Radiographic Signs of Tooth Resorption and Hypercementosis in an Equine Model. Biomedicines 2022, 10, 2914. Biomedicines 2023 Jun 29;11(7).
    doi: 10.3390/biomedicines11071865pubmed: 37509728google scholar: lookup
  3. Borowska M, Jasiński T, Gierasimiuk S, Pauk J, Turek B, Górski K, Domino M. Three-Dimensional Segmentation Assisted with Clustering Analysis for Surface and Volume Measurements of Equine Incisor in Multidetector Computed Tomography Data Sets. Sensors (Basel) 2023 Nov 2;23(21).
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