Support vector machine based high intensity focused ultrasound beam lesion degree classification and recognition.
- Author:
Yanling FENG
1
;
Zhencheng CHEN
;
Jishan HE
;
Shengyou QIAN
Author Information
1. Department of Biomedical Engineering, School of Info-Physics and Geomatics Engineering, Central South University, Changsha 410083, China. kfeng52@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Diagnostic Imaging;
methods;
High-Intensity Focused Ultrasound Ablation;
adverse effects;
Humans;
Pattern Recognition, Automated;
methods;
Support Vector Machine
- From:
Journal of Biomedical Engineering
2010;27(5):978-983
- CountryChina
- Language:Chinese
-
Abstract:
Ultrasound based tissue thermal lesion non-invasive detection is of great significance in high intensity focused ultrasound (HIFU) clinical application. In this paper, we propose a sub-pixel method to quantify the ultrasound image change caused by HIFU as correlation-distance. The support vector machine (SVM) was trained by using correlation distance as samples, and the recognition effect was tested. Results showed that sub-pixel cross-correlation vector field could reflect the ablation lesions position. SVM based classification method can recognize HIFU beam lesion degree effectively.
