Abstract
This paper presents a feature-guided approach for shape-based interpolation of porous and tortuous binary objects. The feature points derived from the boundaries of the candidate source objects are matched non-linearly. The intermediate objects are obtained by appropriately blending the warped source objects. A robust outlier-rejecting, non-linear point matching algorithm based on thin-plate splines is used for establishing the feature correspondence. The proposed scheme correctly handles objects with holes, large offsets and drastic invaginations. Preliminary results suggest that this approach could be used to significantly enhance the sparse Talairach-Tournoux brain atlas.
Original language | English (US) |
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Pages (from-to) | 957-958 |
Number of pages | 2 |
Journal | Lecture Notes in Computer Science |
Volume | 2879 |
Issue number | PART 2 |
DOIs | |
State | Published - 2003 |
Event | Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada Duration: Nov 15 2003 → Nov 18 2003 |
ASJC Scopus subject areas
- Theoretical Computer Science
- General Computer Science