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Home / Equine Research Bank / BMC Vet Res / A novel approach to thermographic images analysis of equine ...
BMC veterinary research2021; 17(1); 99; doi: 10.1186/s12917-021-02803-2

A novel approach to thermographic images analysis of equine thoracolumbar region: the effect of effort and rider’s body weight on structural image complexity.

Abstract: The horses' backs are particularly exposed to overload and injuries due to direct contact with the saddle and the influence of e.g. the rider's body weight. The maximal load for a horse's back during riding has been suggested not to exceed 20% of the horses' body weight. The common prevalence of back problems in riding horses prompted the popularization of thermography of the thoracolumbar region. However, the analysis methods of thermographic images used so far do not distinguish loaded horses with body weight varying between 10 and 20%. Results: The superficial body temperature (SBT) of the thoracolumbar region of the horse's back was imaged using a non-contact thermographic camera before and after riding under riders with LBW (low body weight, 10%) and HBW (high body weight, 15%). Images were analyzed using six methods: five recent SBT analyses and the novel approach based on Gray Level Co-Occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM). Temperatures of the horse's thoracolumbar region were higher (p  0.05), regardless of used SBT analysis method. Effort-dependent differences (p < 0.05) were noted for six features of GLCM and GLRLM analysis. The values of selected GLCM and GLRLM features also differed (p < 0.05) between the LBW and HBW groups. Conclusions: The GLCM and GLRLM analyses allowed the differentiation of horses subjected to a load of 10 and 15% of their body weights while horseback riding in contrast to the previously used SBT analysis methods. Both types of analyzing methods allow to differentiation thermal images obtained before and after riding. The textural analysis, including selected features of GLCM or GLRLM, seems to be promising tools in considering the quantitative assessment of thermographic images of horses' thoracolumbar region.
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Publication Date: 2021-03-02 PubMed ID: 33653346PubMed Central: PMC7923647DOI: 10.1186/s12917-021-02803-2Google Scholar: Lookup
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  • Journal Article

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 research article focuses on a novel way to analyze thermographic images of horse’s backs to assess the impact of a rider’s body weight and the exertion of effort on the structure of the horse’s back.

Study Purpose and Methodology

  • The research focuses on examining the effect of the rider’s body weight and exertion on the thermographic images of the thoracolumbar region of the horses’ back. This is because horses’ backs are especially exposed to overload and injuries due to the saddle and the impact of the rider’s body weight.
  • To ensure the health of the horse, it has been suggested that the maximum load on a horse’s back should not surpass 20% of the horse’s body weight.
  • Thermography of the thoracolumbar region has become a common method of detecting back problems in riding horses.
  • However, the existing analysis methods of thermographic imaging do not differentiate between horses carrying riders whose body weights fluctuate between 10% and 20% of the horse’s body weight.
  • To offer a clearer differentiation, the researchers used six methods to analyze thermographic images. These included five existing methods plus a novel method involving the Gray Level Co-Occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRLM).

Key Findings

  • Experiments showed that the horse’s thoracolumbar region temperatures were higher after training, but they did not vary based on the rider’s body weight. This finding was consistent across all the superficial body temperature (SBT) analysis methods used.
  • The GLCM and GLRLM analysis methods found differences based on the effort exerted. These differences could be noted in six features of the GLCM and GLRLM analysis. Meanwhile, these two analysis methods also identified differences between horses carrying lighter (LBW – 10%) and heavier (HBW – 15%) riders.

Conclusions

  • The research concludes that the GLCM and GLRLM analyses allow for differentiation between horses subject to riders of different body weights that make up 10 and 15% of their own body weights.
  • Both types of analysis methods can differentiate thermal images obtained before and after riding.
  • Therefore, textural analysis involving selected features of the GLCM or GLRLM can offer promising tools in the quantitative assessment of thermographic images of horses’ thoracolumbar region.

Cite This Article

APA
Masko M, Borowska M, Domino M, Jasinski T, Zdrojkowski L, Gajewski Z. (2021). A novel approach to thermographic images analysis of equine thoracolumbar region: the effect of effort and rider’s body weight on structural image complexity. BMC Vet Res, 17(1), 99. https://doi.org/10.1186/s12917-021-02803-2

Publication

BMC veterinary research
ISSN: 1746-6148
NlmUniqueID: 101249759
Country: England
Language: English
Volume: 17
Issue: 1
Pages: 99
PII: 99

Researcher Affiliations

Masko, Malgorzata
  • Department of Animal Breeding, Institute of Animal Science, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland.
Borowska, Marta
  • Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Bialystok, Poland.
Domino, Malgorzata
  • Department of Large Animal Diseases and Clinic, Veterinary Research Centre and Center for Biomedical Research, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland. malgorzata_domino@wp.pl.
Jasinski, Tomasz
  • Department of Large Animal Diseases and Clinic, Veterinary Research Centre and Center for Biomedical Research, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland.
Zdrojkowski, Lukasz
  • Department of Large Animal Diseases and Clinic, Veterinary Research Centre and Center for Biomedical Research, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland.
Gajewski, Zdzislaw
  • Department of Large Animal Diseases and Clinic, Veterinary Research Centre and Center for Biomedical Research, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland.

MeSH Terms

  • Animals
  • Back / physiology
  • Body Weight
  • Female
  • Horses / physiology
  • Humans
  • Male
  • Physical Conditioning, Animal
  • Skin Temperature
  • Thermography / veterinary

Grant Funding

  • WZ/WM-IIB/1/2020 / Ministerstwo Nauki i Szkolnictwa Wyu017cszego

Conflict of Interest Statement

The authors declare no conflicts of interest.

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Citations

This article has been cited 6 times.
  1. Domino M, Borowska M, Zdrojkowski Ł, Jasiński T, Sikorska U, Skibniewski M, Maśko M. Application of the Two-Dimensional Entropy Measures in the Infrared Thermography-Based Detection of Rider: Horse Bodyweight Ratio in Horseback Riding. Sensors (Basel) 2022 Aug 13;22(16).
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  2. Górski K, Borowska M, Stefanik E, Polkowska I, Turek B, Bereznowski A, Domino M. Selection of Filtering and Image Texture Analysis in the Radiographic Images Processing of Horses' Incisor Teeth Affected by the EOTRH Syndrome. Sensors (Basel) 2022 Apr 11;22(8).
    doi: 10.3390/s22082920pubmed: 35458905google scholar: lookup
  3. Domino M, Borowska M, Kozłowska N, Trojakowska A, Zdrojkowski Ł, Jasiński T, Smyth G, Maśko M. Selection of Image Texture Analysis and Color Model in the Advanced Image Processing of Thermal Images of Horses following Exercise. Animals (Basel) 2022 Feb 12;12(4).
    doi: 10.3390/ani12040444pubmed: 35203152google scholar: lookup
  4. Domino M, Borowska M, Trojakowska A, Kozłowska N, Zdrojkowski Ł, Jasiński T, Smyth G, Maśko M. The Effect of Rider:Horse Bodyweight Ratio on the Superficial Body Temperature of Horse's Thoracolumbar Region Evaluated by Advanced Thermal Image Processing. Animals (Basel) 2022 Jan 13;12(2).
    doi: 10.3390/ani12020195pubmed: 35049815google scholar: lookup
  5. Domino M, Borowska M, Kozłowska N, Zdrojkowski Ł, Jasiński T, Smyth G, Maśko M. Advances in Thermal Image Analysis for the Detection of Pregnancy in Horses Using Infrared Thermography. Sensors (Basel) 2021 Dec 28;22(1).
    doi: 10.3390/s22010191pubmed: 35009733google scholar: lookup
  6. Domańska-Kruppa N, Wierzbicka M, Stefanik E. Advances in the Clinical Diagnostics to Equine Back Pain: A Review of Imaging and Functional Modalities. Animals (Basel) 2024 Feb 23;14(5).
    doi: 10.3390/ani14050698pubmed: 38473083google scholar: lookup
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