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.
Algorithms ; Diagnostic Imaging ; methods ; High-Intensity Focused Ultrasound Ablation ; adverse effects ; Humans ; Pattern Recognition, Automated ; methods ; Support Vector Machine