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.
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© 2003 Springer-Verlag Berlin Heidelberg
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Rajagopalan, S., Karwoski, R.A., Robb, R.A. (2003). Shape-Based Interpolation of Porous and Tortuous Binary Objects. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_121
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DOI: https://doi.org/10.1007/978-3-540-39903-2_121
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20464-0
Online ISBN: 978-3-540-39903-2
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