Stifle joint issues are a major cause of lameness in dogs and it can be a significant marker for various forms of diseases or injuries. A known Tibial Plateau Angle (TPA) helps in the reduction of the diagnosis time of the cause. With the state of the art object detection algorithm YOLO, and its variants, this paper delves into identifying joints, their centroids and other regions of interest to draw multiple line axes and finally calculating the TPA. The methods investigated predicts successfully the TPA within the normal range for 80 percent of the images.
翻译:硬质联合问题是狗出现瘸子的主要原因,它可以成为各种疾病或伤害的重要标志。已知的Tibial Plateau Angle(TPA)有助于缩短病因的诊断时间。根据先进的天体检测算法YOLO及其变体,本文探究了如何辨别关节、它们的机器人和其他感兴趣的区域,以绘制多条线轴并最终计算TPA。调查的方法预测TPA在正常范围内成功达到80%的图像。