Department of Animal Breeding, Institute of Animal Science, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland.
Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Bialystok, Poland.
BMC Vet Res. 2021 Mar 2;17(1):99. doi: 10.1186/s12917-021-02803-2.
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%.
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 < 0.0001) after then before the training, and did not differ depending on the rider's body weight (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.
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.
由于直接与鞍座接触以及骑手体重等因素的影响，马的背部特别容易承受过载和损伤。有人建议，马在骑行时背部的最大负荷不应超过马体重的 20%。骑马中背部问题的普遍存在促使人们普及了胸腰椎区的热成像技术。然而，迄今为止使用的热成像图像分析方法无法区分体重在 10%至 20%之间的负重马。
使用非接触式热像仪在骑手体重分别为 LBW（低体重，10%）和 HBW（高体重，15%）时，在骑马前后对马背部的胸腰椎区进行了浅表体温（SBT）成像。使用五种最新的 SBT 分析方法和基于灰度共生矩阵（GLCM）和灰度行程长度矩阵（GLRLM）的新方法对图像进行了分析。马的胸腰椎区在训练后比训练前的温度更高（p<0.0001），并且与骑手的体重无关（p>0.05），无论使用哪种 SBT 分析方法。GLCM 和 GLRLM 分析中的六个特征均显示出与用力相关的差异（p<0.05）。LBW 和 HBW 组之间的选定 GLCM 和 GLRLM 特征值也存在差异（p<0.05）。
与之前使用的 SBT 分析方法相比，GLCM 和 GLRLM 分析可区分在骑马时承受 10%和 15%体重的马。两种类型的分析方法都可以区分骑马前后获得的热图像。纹理分析，包括 GLCM 或 GLRLM 的选定特征，似乎是对马胸腰椎区热成像进行定量评估的有前途的工具。
