Laser scanner for 3D reconstruction of a wound's edge and topology.

Abstract

Robotic systems have the potential to overcome inherent limitations of humans and offer substantial advantages to patients including reduction in surgery time. Our group has undertaken the challenge of developing autonomous wound closure system. One of the initial steps is to allow accurate assessment of wound skin topology and wound edge location. We present a vision-laser scanner to generate 3D point cloud for 3D reconstruction of wound's edge and topology. When the laser range sensor measures Z coordinate, two encoders installed on the actuators of the gantry robot provide the precision values of X, Y coordinates simultaneously. The 3D point cloud of the wound skin is generated by recordings of X, Y and Z during scanning is performed over wound skin surface. To reduce the scanning time, we exploit a supplementary laser LED to project a regular laser spot on the wound skin surface, which can provide an additional measurement point by incorporating artificial neural network estimation approach. In the meantime, the point cloud of the wound edge can be extracted by detecting if the laser spot is located on the wound edge in the image from 2D camera. The mean absolute error (MAE) and standard deviation (σ) of wound edge are measured in MeshLab environment. The MAE (σ) in X (tangent), Y (tangent), and Z (normal) are 0.32 (0.22) mm, 0.37 (0.34) mm, and 0.61 (0.29) mm, respectively. The experimental results demonstrate that the vision-laser scanner attains high accuracy in determining wound edge location along the tangent of the wound skin. A vision-laser scanner is developed for 3D reconstruction of wound's edge and topology. The experimental tests on the different wound models revealed the effectiveness of the vision-laser scanner. The proposed scanner can generate 3D point cloud of the wound skin and its edge simultaneously, and thus significantly improve the accuracy of wound closure in clinical applications.