A graph cuts-based interactive method for segmentation of magnetic resonance images of meningioma.
- Author:
Shuan-qiang LI
1
;
Qian-jin FENG
;
Wu-fan CHEN
;
Ya-zhong LIN
Author Information
1. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China. lishuanqiang@gmail.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Humans;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Imaging, Three-Dimensional;
methods;
Magnetic Resonance Imaging;
methods;
Meningeal Neoplasms;
diagnosis;
pathology;
Meningioma;
diagnosis;
pathology;
Pattern Recognition, Automated;
methods
- From:
Journal of Southern Medical University
2011;31(7):1164-1168
- CountryChina
- Language:Chinese
-
Abstract:
For accurate segmentation of the magnetic resonance (MR) images of meningioma, we propose a novel interactive segmentation method based on graph cuts. The high dimensional image features was extracted, and for each pixel, the probabilities of its origin, either the tumor or the background regions, were estimated by exploiting the weighted K-nearest neighborhood classifier. Based on these probabilities, a new energy function was proposed. Finally, a graph cut optimal framework was used for the solution of the energy function. The proposed method was evaluated by application in the segmentation of MR images of meningioma, and the results showed that the method significantly improved the segmentation accuracy compared with the gray level information-based graph cut method.
