Computer-assisted lesion detection system for stomach screening using stomach shape and appearance models

摘要

In Japan, stomach cancer is one of the three most common causes of death from cancer. Since periodic health checks of stomach X-rays have become more widely carried out, the physicians' burdens have been increasing in the mass screening to detect initial symptoms of a disease. For the purpose of automatic diagnosis, we try to develop a computer-assisted lesion detection system for stomach screening. The proposed system has two databases. One is the stomach shape database that consists of the computer graphics stomach 3D models based on biomechanics simulation and their projected 2D images. The other is the normal appearance database that is constructed by learning patterns in a normal patient training set. The stomach contour is extracted from an X-ray image including a barium filled region by the following steps. Firstly, the approximated stomach region is obtained by nonrigid registration based on mutual information. We define nonrigid transformation as one that includes translations, rotations, scaling, air-barium interface and weights of eigenvectors determined by principal components analysis in the stomach shape database. Secondly, the accurate stomach contour is extracted from the gradient of an image by using the Dynamic Programming. After then, stomach lesions are detected by inspecting whether the Mahalanobis distance from the mean in the normal appearance database is longer than a suitable value on the extracted stomach contour. We applied our system to 75 X-ray images of barium-filled stomach to show its validity.