Mucosal region detection and 3D reconstruction in wireless capsule endoscopy videos using active contours

Abstract

Wireless capsule endoscopy (WCE) provides an inner view of the human digestive system. The inner tubular like structure of the intestinal tract consists of two major regions: lumen - intermediate region where the capsule moves, mucosa - membrane lining the lumen cavities. We study the use of the Split Bregman version of the extended active contour model of Chan and Vese for segmenting mucosal regions in WCE videos. Utilizing this segmentation we obtain a 3D reconstruction of the mucosal tissues using a near source perspective shape-from-shading (SfS) technique. Numerical results indicate that the active contour based segmentation provides better segmentations compared to previous methods and in turn gives better 3D reconstructions of mucosal regions.

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

“…In Figure 2, we show some example polyps (selected from images shown in Figure 1) in 3D using the shape from shading techniques [30], indicating the amount of protrusion out of the mucosa surface (visualizations as 3D figures are available in the Supplementary Materials and also at the project website). Figure 3 shows a pedunculated polyp that appears in consecutive frames from a VCE exam of a patient.…”

“…Examples of polyps: (a) pedunculated/stalked or subpedunculated; (b) sessile. We show a 3D representation of VCE frames obtained using shapes from shading techniques [30].…”

“…Technique [34] Log-Gabor filter [59] Vascularization + Frangi vesselness [37] Curvature center ratio + K-means clustering [40] Protrusion measure via curvatures [60] K-means clustering + localizing active contour [61] Alpha divergence based active contours [62] Alpha divergence based active contours [30] Active contours + Shape from shading [63] Active contours [64] Active contours…”

“…Prasath et al [30] used an active contours without edges method for identifying mucosal surface in conjunction with shape from shading technique (see also [65]). Eskandari et al [63] used a region based active contour model to segment the polyp region from a given image that contain a polyp (see also [64]).…”

“…Table 2 summarizes the methods available for polyp localization and segmentation so far. A preliminary mucosa segmentation [30,[65][66][67] may be required before applying the polyp segmentation step in order to avoid these non-polyp pixels. …”