Hierarchical Cell Structures for Segmentation of Voxel Images

We compare three hierarchical structures, S15, C15, C19, that are used to steer a segmentation process in 3d voxel images. There is an important topological difference between C19 and both others that we will study. A quantitative evaluation of the quality of the three segmentation techniques based on several hundred experiments is presented.

[1]  Maximilian Reiser,et al.  Segmentation of MR images with B-spline snakes. A multi-resolution approach using the distance transformation for model forces , 1998, Bildverarbeitung für die Medizin.

[2]  J Sijbers,et al.  Watershed-based segmentation of 3D MR data for volume quantization. , 1997, Magnetic resonance imaging.

[3]  Lutz Priese,et al.  3D-Color-Structure-Code - A Hierarchical Region Growing Method for Segmentation of 3D-Images , 2003, SCIA.

[4]  Leszek Wojnar,et al.  Image Analysis , 1998 .

[5]  Thomas Martin Deserno,et al.  Bildverarbeitung für die Medizin: Grundlagen, Modelle, Methoden, Anwendungen , 1997, Bildverarbeitung für die Medizin.

[6]  S. Eiho,et al.  Processing of RI-Angiocardiographic Images , 1976 .

[7]  Isabelle Bloch,et al.  Segmentation of 3D head MR images using morphological reconstruction under constraints and automatic selection of markers , 2001, Proceedings 2001 International Conference on Image Processing (Cat. No.01CH37205).

[8]  Lutz Priese,et al.  A Fast Hybrid Color Segmentation Method , 1993, DAGM-Symposium.

[9]  G. Hartmann.  Recognition of Hierarchically encoded images by technical and biological systems , 2004, Biological Cybernetics.

[10]  Pierre Hellier,et al.  Segmentation of brain 3D MR images using level sets and dense registration , 2001, Medical Image Anal..

[11]  Larry S. Davis,et al.  A new class of edge-preserving smoothing filters , 1987, Pattern Recognit. Lett..

[12]  Olaf Dössel,et al.  Modellbasierte Segmentation klinischer MR-Aufnahmen , 1998, Bildverarbeitung für die Medizin.