Image-Based Flexible Endoscope Steering

Manually steering the tip of a flexible endoscope to navigate through an endoluminal path relies on the physician’s dexterity and experience. In this paper we present the realization of a robotic flexible endoscope steering system that uses the endoscopic images to control the tip orientation towards the direction of the lumen. Two image-based control algorithms are investigated, one is based on the optical flow and the other is based on the image intensity. Both are evaluated using simulations in which the endoscope was steered through the lumen. The RMS distance to the lumen center was less than 25% of the lumen width. An experimental setup was built using a standard flexible endoscope, and the image-based control algorithms were used to actuate the wheels of the endoscope for tip steering. Experiments were conducted in an anatomical model to simulate gastroscopy. The image intensity- based algorithm was capable of steering the endoscope tip through an endoluminal path from the mouth to the duodenum accurately. Compared to manual control, the robotically steered endoscope performed 68% better in terms of keeping the lumen centered in the image

The Pq-Histogram as a Navigation Clue

We propose a novel visual clue for navigation, in which the local 3D information or (p, q) is summarised in a single structure, called pq-histogram. The pq-histogram is obtained by discretising in logarithmic scale the local depth (p, q). Since this histogram gives a global view of the scene, it could be used as a fast clue for navigation. An arrangement of four pq-histograms, one for each image quadrant, can advise many orientations. The potential application of the pq-histogram is illustrated in two domains. Firstly, semi-automatic navigation of an endoscope inside the human colon. Secondly, mobile robot navigating in certain environments, such as corridors and mines. In both cases, the method was tested with real images with encouraging results