利用功率多普勒超声血流信息自动检测前列腺癌

Chuan-Yu Chang, Ching-Fong You, Y. Tsai
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引用次数: 0

摘要

与良性前列腺相比,恶性前列腺具有较高的峰值收缩速度、较低的舒张末期速度和阻力指数。在这些血流信息中,舒张末期速度更为一致和显著。本文提出了一种利用功率多普勒超声血流信息自动检测前列腺癌的方法。采用活动轮廓模型对前列腺区域进行半自动分割。将左、右外周区的平均流速、阻力指数和舒张末期流速组合成特征向量。因此,使用支持向量机对前列腺进行恶性或良性分类。实验结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic Prostate Cancer Detection Using Blood Flow Information in Power Doppler Ultrasonography
Compared with the benign prostate, the malignant prostate has higher peak systolic velocity, lower end diastolic velocity and resistance index. In these blood flow information, the end diastolic velocity is more consistent and significant. In this paper, an automatic prostate cancer detection using blood flow information in power Doppler ultrasonography is proposed. The prostate region was segmented semi-automatically by the active contour model. The average velocity, resistance index and end diastolic velocity obtained from left and right peripheral zone were combined to form a feature vector. Accordingly, a support vector machine is used to classify the prostate as malignant or benign. Experimental results demonstrate the effectiveness of the proposed approach.
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