Title
A variable baseline stereoscopic camera with fast deployable structure for natural orifice transluminal endoscopic surgery
Abstract
Purpose Stereo vision can provide surgeons with 3D images and reduce the difficulty of operation in robot-assisted surgery. In natural orifice transluminal endoscopic surgery, distortions of the stereoscopic images could be induced at different observation depths. This would increase the risk of surgery. We proposed a novel camera to solve this problem. Methods This study integrated the camera calibration matrix and the geometric model of stereoscopic system to find the cause of distortion. It was found that image distortions were caused by inappropriate disparity, and this could be avoided by changing the camera baseline. We found the relationship between camera baseline and observation depth with the model. A variable baseline stereoscopic camera with deployable structure was designed to achieve this requirement. The baseline could be adjusted to provide appropriate disparity. Results Three controlled experiments were conducted to verify the stereo vision of the proposed camera at different observation depths. No significant difference was observed in the completion time. At the observation depths of 30 mm and 90 mm, the number of errors apparently decreased by 62.90% and 51.06%, respectively. Conclusions The significant decrease in number of errors shows that the proposed camera has a better stereo vision than a regular camera at both small and large observation depths. It can produce more accurate stereoscopic images at any depth. This will further improve the safety of robot-assisted surgery.
Year
DOI
Venue
2022
10.1007/s11548-021-02509-8
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY
Keywords
DocType
Volume
Minimally invasive surgery, Surgical robotics, Natural orifice transluminal endoscopic surgery, Stereoscopic vision, Stereoscopic camera
Journal
17
Issue
ISSN
Citations 
1
1861-6410
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Xinan Sun100.34
he su231.07
Jinhua Li300.68
Shuxin Wang44411.24