Hierarchical deformable model using statistical and geometric information

Dinggang Shen, Christos Davatzikos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

A new deformable model has been proposed by employing a hierarchy of affine transformations and an adaptive-focus statistical model. An attribute vector is used to characterize the geometric structure in the vicinity of each point of the model; the deformable model then deforms in a way that seeks regions with the similar attribute vectors. This is in contrast to most active contour models, which deform to nearby edges without considering the geometric structure of the boundary around an edge point. Furthermore, a deformation mechanism that is robust to local minima is proposed, which is based on evaluating the snake energy function on segments of the snake at a time, instead of individual points. Various experimental results show the effectiveness of the proposed methodology.

Original languageEnglish
Title of host publicationProceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis
Place of PublicationLos Alamitos, CA, United States
PublisherIEEE
Pages146-153
Number of pages8
Publication statusPublished - 2000 Jan 1
Externally publishedYes
EventMMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis - Hilton Head Island, SC, USA
Duration: 2000 Jun 112000 Jun 12

Other

OtherMMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis
CityHilton Head Island, SC, USA
Period00/6/1100/6/12

Fingerprint

Deformable Models
Hierarchical Model
Snakes
Geometric Structure
Attribute
Active Contour Model
Energy Function
Local Minima
Statistical Model
Affine transformation
Methodology
Experimental Results
Model

ASJC Scopus subject areas

  • Analysis

Cite this

Shen, D., & Davatzikos, C. (2000). Hierarchical deformable model using statistical and geometric information. In Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis (pp. 146-153). Los Alamitos, CA, United States: IEEE.

Hierarchical deformable model using statistical and geometric information. / Shen, Dinggang; Davatzikos, Christos.

Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. Los Alamitos, CA, United States : IEEE, 2000. p. 146-153.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Shen, D & Davatzikos, C 2000, Hierarchical deformable model using statistical and geometric information. in Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. IEEE, Los Alamitos, CA, United States, pp. 146-153, MMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, Hilton Head Island, SC, USA, 00/6/11.
Shen D, Davatzikos C. Hierarchical deformable model using statistical and geometric information. In Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. Los Alamitos, CA, United States: IEEE. 2000. p. 146-153
Shen, Dinggang ; Davatzikos, Christos. / Hierarchical deformable model using statistical and geometric information. Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis. Los Alamitos, CA, United States : IEEE, 2000. pp. 146-153
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