Brief Article
Copyright ©2013 Baishideng Publishing Group Co.
World J Gastroenterol. Nov 28, 2013; 19(44): 8028-8033
Published online Nov 28, 2013. doi: 10.3748/wjg.v19.i44.8028
Figure 1
Figure 1 Shape-from-Shading function. Capturing a surface using a camera removes depth information. Shape-from-Shading (SfS) techniques try to reproduce the missing depth information from a given two-dimensional (2-D) image.
Figure 2
Figure 2 For the evaluation phase, a Mathworks© Matlab program with a graphic user interface was developed. The program consists of two windows in which the conventional two-dimensional capsule endoscopy image (single frame at the right side/window of the graphic user interface screen) and its corresponding three-dimensional represented images (four, one for each of the 4 shape-from-shading under evaluation) were presented to the reviewer.
Figure 3
Figure 3 Assessment results for the 4 Shape-from-Shading algorithms per lesion category.
Figure 4
Figure 4 Ciuti’s algorithm (left) and Tsai’s method (right). Although Tsai’s method is very straightforward and to an extent simplistic, it provides satisfying results. Ciuti’s et al[16] algorithm, on the other hand, uses a more advanced model that makes things in the background appear darker than in Tsai’s model.