SHAPE PRIOR BASED ON STATISTICAL MAP FOR ACTIVE CONTOUR SEGMENTATION

被引：6

作者：

Houhou, Nawal ^{[1
]}

Lemkaddem, Alia ^{[1
]}

Duay, Valerie ^{[1
]}

Allal, Abdelkarim ^{[2
]}

Thiran, Jean-Philippe ^{[1
]}

机构：

[1] Ecole Polytech Fed Lausanne, Signal Proc Lab LTS5, CH-1015 Lausanne, Switzerland

[2] Univ Hosp Geneva, Div Radiat Oncol, Geneva, Switzerland

来源：

2008 15TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, VOLS 1-5 | 2008年

关键词：

Statistical shape; active contour segmentation;

D O I：

10.1109/ICIP.2008.4712247

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

We propose a new method for performing active contour segmentation based on the statistical prior knowledge of the object to detect. From a binary training set of objects, a statistical map describes the possible shapes of the object by computing the probability for each point to belong to the object. This statistical map is treated as a prior distribution and an energy functional is defined such that the object reaches the most probable shape knowing the model. The optimization is done in the level-set framework. Results on both synthetic and medical images are shown.

引用

页码：2284 / 2287

页数：4

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