LIVER SEGMENTATION BASED ON DEFORMABLE REGISTRATION AND MULTI-LAYER SEGMENTATION

被引：3
|
作者：
Badakhshannoory, Hossein [1 ]
Saeedi, Parvaneh [1 ]
Qayumi, Karim [2 ]
机构：
[1] Simon Fraser Univ, Sch Engn Sci, Burnaby, BC V5A 1S6, Canada
[2] Univ British Columbia, Dept Surg, Vancouver, BC, Canada
来源：
2010 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING | 2010年
关键词：
Liver segmentation; 3D organ reconstruction; deformable registration; mean shift segmentation;
D O I：
10.1109/ICIP.2010.5653531
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This paper describes a semi-automatic algorithm for extracting liver masks of CT scan volumes. The proposed method relies on two types of information: liver's shape and its intensity characteristics. Here the liver shape information is retained by measuring the shape similarities between consecutive slices of the liver's CT scans. This is done through a deformable registration scheme. The liver intensity is utilized by a multi-layer image segmentation algorithm that emphasizes on the true boundaries of the liver. The proposed algorithm is tested for MICCAI 2007 grand challenge workshop dataset. The average results for volumetric overlap error and relative volume difference is 11.12% and 2.21% respectively.
引用
收藏
页码：2549 / 2552
页数：4
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