Segmentation through Variable-Order Surface Fitting
IEEE Transactions on Pattern Analysis and Machine Intelligence
Surface shape and curvature scales
Image and Vision Computing
Computing the differential characteristics of isointensity surface
Computer Vision and Image Understanding
Model-Based analysis of local shape for lesion detection in CT scans
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Automated detection of small-size pulmonary nodules based on helical CT images
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
SPReAD: on spherical part recognition by axial discretization in 4d hough space
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
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A novel method called local shape controlled voting has been developed for spherical object detection in 3D voxel images. By introducing local shape properties into the voting procedure of normal overlap, the proposed method improves the capability of differentiating spherical objects from other structures, as the normal overlap technique only measures the 'density' of normal overlapping, while how the normals are distributed in 3D is not discovered. The proposed method was applied to computer aided detection of pulmonary nodules based on helical CT images. Experiments showed that this method attained a better performance compared to the original normal overlap technique.