Computerized detection of pulmonary nodules using a combination of 3D global and local shape information based on helical CT images

Abstract

A novel method called local shape controlled voting has been developed for spherical object detection in 3D voxel images. By combining local shape properties into the global tracking procedure of normal overlap, the proposed method solved the ambiguities of normal overlap between a small size sphere and a possible large size cylinder, as the normal overlap technique can only measures the 'density' of normal overlapping, while how the normal vectors are distributed in 3D is not discovered. The proposed method was applied to computer aided detection of small size pulmonary nodules based on helical CT images. Experiments showed that this method attained a better performance compared to the original normal overlap technique.