A Fast Anisotropic Mumford-Shah Functional Based Segmentation

被引：0

作者：

Garamendi, J. F. ^{[1
]}

Malpica, N. ^{[1
]}

Schiavi, E. ^{[1
]}

机构：

[1] Univ Rey Juan Carlos, Madrid, Spain

来源：

PATTERN RECOGNITION AND IMAGE ANALYSIS, PROCEEDINGS | 2009年 / 5524卷

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Digital (binary) image segmentation is a critical step in most image processing protocols, especially in medical imaging where accurate and fast segmentation and classification are a challenging issue. In this paper we present a fast relaxation algorithm to minimize an anistropic Mumford-Shah energy functional for piecewise constant approximation of corrupted data. The algorithm is tested with synthetic phantoms and some CT images of the abdomen. Our results are finally compared with manual segmentations in order to validate the proposed model.

引用

页码：322 / 329

页数：8

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