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Using Deformable Surface to Segment 3-D images and Infer Differential Structures

Cohen, Isaac; Cohen, Laurent D.; Ayache, Nicholas (1992), Using Deformable Surface to Segment 3-D images and Infer Differential Structures, in Sandini, G., Computer Vision — ECCV'92 Second European Conference on Computer Vision Santa Margherita Ligure, Italy, May 19–22, 1992 Proceedings, Springer : Berlin Heidelberg, p. 648--652. 10.1007/3-540-55426-2_69

Type
Communication / Conférence
External document link
https://hal.inria.fr/inria-00615537
Date
1992
Conference title
ECCV'92 Second European Conference on Computer Vision
Conference date
1992-05
Conference city
Santa Margherita Ligure
Conference country
Italy
Book title
Computer Vision — ECCV'92 Second European Conference on Computer Vision Santa Margherita Ligure, Italy, May 19–22, 1992 Proceedings
Book author
Sandini, G.
Publisher
Springer
Published in
Berlin Heidelberg
ISBN
978-3-540-55426-4
Pages
648--652
Publication identifier
10.1007/3-540-55426-2_69
Metadata
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Author(s)
Cohen, Isaac

Cohen, Laurent D.

Ayache, Nicholas
Abstract (EN)
In this paper, we generalize the deformable model [4, 7] to a 3-D model, which evolves in 3-D images, under the action of internal forces (describing some elasticity properties of the surface), and external forces attracting the surface toward some detected edgels. Our formalism leads to the minimization of an energy which is expressed as a functional. We use a variational approach and a finite element method to actually express the surface in a discrete basis of continuous functions. This leads to a reduced computational complexity and a better numerical stability.The power of the present approach to segment 3-D images is demonstrated by a set of experimental results on various complex medical 3-D images.Another contribution of this approach is the possibility to infer easily the differential structure of the segmented surface. As we end-up with an analytical description of the surface, this allows to compute for instance its first and second fundamental forms. From this, one can extract a curvature primal sketch of the surface, including some intrinsic features which can be used as landmarks for 3-D image interpretation.
Subjects / Keywords
medical 3-D images

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