Title :
Centerline Extraction Based on Hessian Matrix and Scale Space Analysis
Author :
Lv, Xinrong ; Gao, Xinbo
Author_Institution :
Coll. of Inf. & Control Eng., China Univ. of Pet. (East China), Dongying, China
Abstract :
In order to extract the medial axes of vascular objects from 3D medical volume data, a precise centerline extraction algorithm is proposed. A binary image sequence which has been segmented is taken as the input data. Distance transform is performed for the data to generate a distance map. Based on the distance map and for each target-voxel which belongs to the cavity of vascular structure, a Hessian matrix is computed. By judging the eigenvalues and eigenvectors of Hessian matrix for each target-voxel, a coarse centerline is extracted according to some rules. After modifying all points in the coarse centerline by using scale space analysis, a precise centerline will be obtained. The experimental results illustrate the simplicity of Hessian matrix extraction and the precision of scale space analysis. And the whole centerline extraction algorithm has been applied to 3D medical volume data visualization-virtual endoscopy.
Keywords :
Hessian matrices; data visualisation; eigenvalues and eigenfunctions; feature extraction; image sequences; medical image processing; state-space methods; 3D medical volume data; 3D medical volume data visualization; Hessian matrix extraction; binary image sequence; coarse centerline extraction; distance map; distance transform; eigenvalues and eigenvectors; scale space analysis; target voxel; vascular object medial axes extraction; vascular structure cavity; virtual endoscopy; Biomedical imaging; Data mining; Eigenvalues and eigenfunctions; Endoscopes; Euclidean distance; Image segmentation; Image sequences; Inspection; Medical diagnostic imaging; Topology;
Conference_Titel :
Information Engineering and Computer Science, 2009. ICIECS 2009. International Conference on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-4994-1
DOI :
10.1109/ICIECS.2009.5363502