【摘要】 基于超声的组织损伤无损检测在高强度聚焦超声(HIFU)的临床推广与应用中具有重要意义。提出一种亚像素级方法将HIFU束损伤所导致的图像变化程度量化为相关距离。采用相关距离作为样本进行基于支持向量机(SVM)的HIFU束损伤程度分类训练,并对方法进行分类识别检验。实验结果表明,超声图像亚像素级相关分析矢量场可反映组织发生凝固性坏死的位置,基于SVM的分类算法可有效识别HIFU束损伤程度。更多还原

【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.更多还原