A Fast, Semi-Automatic Brain Structure Segmentation Algorithm for Magnetic Resonance Imaging

被引:12
|
作者
Karsch, Kevin [1 ]
He, Qing [1 ]
Duan, Ye [1 ]
机构
[1] Univ Missouri, Dept Comp Sci, Columbia, MO 65211 USA
来源
2009 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE | 2009年
关键词
segmentation; visualization; validation; MRI; ACTIVE CONTOUR MODELS; DEFORMABLE MODELS;
D O I
10.1109/BIBM.2009.40
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Medical image segmentation has become an essential technique in clinical and research-oriented applications. Because manual segmentation methods are tedious, and fully automatic segmentation lacks the flexibility of human intervention or correction, semi-automatic methods have become the preferred type of medical image segmentation. We present a hybrid, semi-automatic segmentation method in 3D that integrates both region-based and boundary-based procedures. Our method differs from previous hybrid methods in that we perform region-based and boundary-based approaches separately, which allows for more efficient segmentation. A region-based technique is used to generate an initial seed contour that roughly represents the boundary of a target brain structure, alleviating the local minima problem in the subsequent model deformation phase. The contour is deformed under a unique force equation independent of image edges. Experiments on MRI data show that this method can achieve high accuracy and efficiency primarily due to the unique seed initialization technique.
引用
收藏
页码:297 / 302
页数:6
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