title: [Support vector machine based high intensity focused ultrasound beam lesion degree classification and recognition].
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.
authors.affiliation: Department of Biomedical Engineering, School of Info-Physics and Geomatics Engineering, Central South University, Changsha 410083, China. kfeng52@163.com
authors.forename: Yanling
authors.initials: Y
authors.lastname: Feng
authors.forename: Zhencheng
authors.initials: Z
authors.lastname: Chen
authors.forename: Jishan
authors.initials: J
authors.lastname: He
authors.forename: Shengyou
authors.initials: S
authors.lastname: Qian
mesh_terms: D000465:Algorithms; D003952:Diagnostic Imaging / Q000379:methods; D057086:High-Intensity Focused Ultrasound Ablation / Q000009:adverse effects*; D006801:Humans; D010363:Pattern Recognition, Automated / Q000379:methods*; D060388:Support Vector Machine