Colonoscopy Navigation using End-to-End Deep Visuomotor Control: A User Study

TL;DR

This paper introduces Deep Visuomotor Control (DVC), an autonomous, image-based endoscope control system using deep reinforcement learning, which improves safety and supervision ease in colonoscopy navigation compared to traditional heuristic methods.

Contribution

The work presents a novel deep reinforcement learning approach for autonomous endoscope control that adapts to complex colon environments and enhances supervision for clinicians.

Findings

DVC achieves equivalent navigation performance to expert clinicians.

DVC demonstrates increased safety during procedures.

Novice users find DVC easier to supervise than heuristic policies.

Abstract

Flexible endoscopes for colonoscopy present several limitations due to their inherent complexity, resulting in patient discomfort and lack of intuitiveness for clinicians. Robotic devices together with autonomous control represent a viable solution to reduce the workload of endoscopists and the training time while improving the overall procedure outcome. Prior works on autonomous endoscope control use heuristic policies that limit their generalisation to the unstructured and highly deformable colon environment and require frequent human intervention. This work proposes an image-based control of the endoscope using Deep Reinforcement Learning, called Deep Visuomotor Control (DVC), to exhibit adaptive behaviour in convoluted sections of the colon tract. DVC learns a mapping between the endoscopic images and the control signal of the endoscope. A first user study of 20 expert gastrointestinal endoscopists was carried out to compare their navigation performance with DVC policies using a realistic virtual simulator. The results indicate that DVC shows equivalent performance on several assessment parameters, being more safer. Moreover, a second user study with 20 novice participants was performed to demonstrate easier human supervision compared to a state-of-the-art heuristic control policy. Seamless supervision of colonoscopy procedures would enable interventionists to focus on the medical decision rather than on the control problem of the endoscope.