Paper Info
Title
Multistage adaptive control strategy based on image contour data for autonomous endoscope navigation
Abstract
The physician burnout, poor ergonomics are hardly conducive to the sustainability and high quality of colonoscopy. In order to reduce doctors' workload and improve patients’ experiences during colonoscopy, this paper proposes a multistage adaptive control approach based on image contour data to guide the autonomous navigation of endoscopes. First, a fast image preprocessing and contour extraction algorithms are designed. Second, different processing algorithms are developed according to the different contour information that can be clearly extracted to compute the endoscope control parameters. Third, when a clear contour cannot be extracted, a triple control method inspired by the turning of a novice car driver is devised to help the endoscope capture clear contours. The proposed multistage adaptive control approach is tested in an intestinal model over a variety of curved configurations and verified on the actual colonoscopy image. The results reveal the success of the strategy in both straight sections of this intestinal model and in tightly curved sections as small as 6 cm in radius of curvature. In the experiment, processing time for a single image is 20–25 ms and the accuracy of judging steering based on intestinal model pictures is 96.7%. Additionally, the average velocity reaches 3.04 cm/s in straight sections and 2.49 cm/s in curved sections respectively.
Year
DOI
Venue
2022
10.1016/j.compbiomed.2022.105946
Computers in Biology and Medicine
Keywords
DocType
Volume
Autonomous navigation,Computer-assisted endoscope,Machine vision,Calculation method of colonoscopy image
Journal
149
ISSN
Citations 
PageRank 
0010-4825
0
0.34
References 
Authors
0
8
Name
Order
Citations
PageRank
Mingqiang Li100.34
Boquan Wang200.34
Jianlin Yang300.34
Jia Cao400.34
Chenzhi You500.34
Yizhe Sun600.34
Jing Wang72823.94
Dawei Wu800.34