### 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 language | English (US) |
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Title of host publication | Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis |

Publisher | IEEE |

Pages | 146-153 |

Number of pages | 8 |

State | Published - 2000 |

Event | MMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis - Hilton Head Island, SC, USA Duration: Jun 11 2000 → Jun 12 2000 |

### Other

Other | MMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis |
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City | Hilton Head Island, SC, USA |

Period | 6/11/00 → 6/12/00 |

### Fingerprint

### ASJC Scopus subject areas

- Analysis

### Cite this

*Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis*(pp. 146-153). IEEE.

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

*Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis.*IEEE, pp. 146-153, MMBIA-2000: IEEE Workshop on Mathematical Methods in Biomedical Image Analysis, Hilton Head Island, SC, USA, 6/11/00.

}

TY - GEN

T1 - Hierarchical deformable model using statistical and geometric information

AU - Shen, Dinggang

AU - Davatzikos, Christos

PY - 2000

Y1 - 2000

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0033687540&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033687540&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:0033687540

SP - 146

EP - 153

BT - Proceedings of the Workshop on Mathematical Methods in Biomedical Image Analysis

PB - IEEE

ER -