Liver CT image segmentation using statistical shape model based on statistical and specific information.
- Author:
Chunli LI
1
;
Jiulou ZHANG
;
Qianjin FENG
Author Information
1. School of Biomedical Engineering, Southern Medical University, Guangzhou, China. lichli1986@126.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Humans;
Imaging, Three-Dimensional;
methods;
Liver;
diagnostic imaging;
Liver Diseases;
diagnostic imaging;
Liver Neoplasms;
diagnostic imaging;
Models, Statistical;
Radiographic Image Interpretation, Computer-Assisted;
methods;
Tomography, X-Ray Computed;
methods
- From:
Journal of Southern Medical University
2012;32(1):23-27
- CountryChina
- Language:Chinese
-
Abstract:
We propose an effective algorithm for accurate 3D segmentation of CT liver images based on statistical and specific information. We present a new intensity model which combines patient-specific intensity information of boundary with the statistical information for liver segmentation. Compared to the traditional methods, our approach not only produces excellent segmentation accuracy, but also increases the robustness.
