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Patterns Detection and Recognition in Visual Aided System for Prosthesis Pose Estimation during Total Hip Replacement Surgery

机译:人工全髋关节置换术中假体姿势估计的视觉辅助系统中的模式检测与识别

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Total hip replacement (THR) surgeries are leading to severe complications such as prosthetic impingement and dislocation. To help surgeons during THR surgery we are developing a real-time visual aided system for an accurate placement of hip prostheses within the safe zone. To ensure the feasibility of this visual aided system in the blood interfering situation during surgery, improved pattern detection and recognition method is proposed in this paper. The mini camera mounted on the femoral head is used to take images of customized patterns designed inside the acetabular cup. Firstly, all the blood-covered patterns are detected. Since the blood is red in color for processing, we extract red channel of the image sequence. For noise elimination, edge preservation and uneven illumination, the median filter and adaptive thresholding is applied respectively. Secondly, recognizing each pattern appeared in the frame by generating its specific 9-bit binary, sampling at each pattern from top left corner to bottom right corner. The simulation results show pattern detection and recognition rate as high as 99%, which validates the efficiency of the proposed method.
机译:全髋关节置换术(THR)导致严重的并发症,例如假肢撞击和脱位。为了在THR手术期间为外科医生提供帮助,我们正在开发一种实时视觉辅助系统,以将髋关节假体准确地放置在安全区域内。为了保证该视觉辅助系统在手术中血液干扰情况下的可行性,提出了一种改进的模式检测与识别方法。安装在股骨头上的微型摄像头用于拍摄髋臼杯内部设计的定制图案的图像。首先,检测所有被血液覆盖的模式。由于血液是红色供处理,因此我们提取图像序列的红色通道。为了消除噪声,保持边缘和照明不均匀,分别应用了中值滤波器和自适应阈值。其次,通过生成特定的9位二进制码来识别帧中出现的每个模式,并在每个模式中从左上角到右下角进行采样。仿真结果表明,模式检测和识别率高达99%,证明了该方法的有效性。

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