解剖特征引导软式内镜机器人自主介入策略研究

An Autonomous Intervention Strategy for Robotic Soft Endoscope Guided by Anatomical Features

以上消化道介入为例,在前期研制的YunSRobot内镜机器人平台上开展软式内镜自主介入策略研究.基于Faster-RCNN算法和数学形态学图像处理方法从镜下图像中提取消化道解剖特征,并设计自主化镜体操控和弯曲定向策略实现内镜在上消化道中的自主介入.在高仿真度的上消化道模型中开展了对照实验,结果表明本文方法的介入成功率为100%.与非专业人员主从介入相比,平均耗时从262.01 s降低到197 s,介入力的最大值从11.8 N降到9.6 N.与专业人员主从介入相比,介入力最大值基本一致,仅多耗时34.33 s.本文提出的自主化介入策略可以拓展到呼吸道、尿道等其他腔道的软式内镜介入.

An autonomous intervention strategy for soft endoscope in upper digestive tract is studied based on the previously designed YunSRobot endoscopic robot. The anatomical features of digestive tract are extracted from the endoscopic images based on the Faster-RCNN(faster-regions with convolutional neural network feature) algorithm and mathematical morphology image processing. Then an autonomous endoscope manipulation and orientation strategy is designed to perform autonomous endoscope intervention in the upper digestive tract. Comparative experiments are carried out on a highly simulated phantom of upper digestive tract, and the results show that the intervention success rate of the proposed method is 100%.Compared with the master-slave control based intervention by the unprofessional operator, the average intervention duration of the autonomous intervention is reduced from 262.01 s to 197 s, and the maximum insertion force is decreased from 11.8 N to 9.6 N. Compared with master-slave control based intervention by the professional operator, the maximum insertion force is almost the same, and the average intervention duration is only 34.33 s longer. The autonomous intervention strategy proposed also can be applied to soft endoscope intervention in other natural orifice such as respiratory and urinary tracts.