Extraction of human stomach using computational geometry
Kazuo Aisaka, Kiyoshi Arai, Kumiko Tsutsui, Akihide Hashizume · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1991
This paper presents a method for extracting the profile of the stomach by computational geometry. The stomach is difficult to recognize from an X-ray because of its elasticity. Global information of the stomach shape is required for recognition. The method has three steps. In the first step, the edge is enhanced, and then edge pieces are found as candidates for the border. Because the resulting border is almost always incomplete, a method for connecting the pieces is required. The second step uses computational geometry to create the global structure from the edge pieces. A Delaunay graph is drawn from the end points of the pieces. This enables us to decide which pieces are most likely to connect. The third step uses the shape of a stomach to find the best sequence of pieces. The knowledge is described in simple LISP functions. Because a Delaunay graph is planar, we can reduce the number of candidate pieces while searching for the most likely sequence. We applied this method to seven stomach pictures taken by the double contrast method and found the greater curvature in six cases. Enhancing the shape knowledge will increase the number of recognizable parts.