Lo Chung-Ming, Chen Yen-Po, Chang Yeun-Chung, Lo Chiao, Huang Chiun-Sheng, Chang Ruey-Feng
Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan, Republic of China.
Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan, Republic of China.
Ultrason Imaging. 2014 Jul;36(3):151-166. doi: 10.1177/0161734613520599. Epub 2014 Jun 3.
Acoustic radiation force impulse (ARFI) is a newly developed elastography technique that uses acoustic radiation force to provide additional stiffness information to conventional sonography. A computer-aided diagnosis (CAD) system was proposed to automatically specify the tumor boundaries in ARFI images and quantify the statistical stiffness information to reduce user dependence. The level-set segmentation was used to delineate tumor boundaries in B-mode images, and the segmented boundaries were then mapped to the corresponding area in ARFI images for a gray-scale calculation. A total of 61 benign and 51 malignant tumors were evaluated in the experiment. The CAD system based on the proposed ARFI features achieved an accuracy of 80% (90/112), a sensitivity of 80% (41/51), and a specificity of 80% (49/61), which is significantly better than that of the quantitative B-mode features (p < 0.05). The ARFI features were further combined with the B-mode features, including shape and texture features, to further improve performance (area under the curve [AUC], 0.90 vs. 0.86). In conclusion, the CAD system based on the proposed ARFI features is a promising and efficient diagnostic method.
声辐射力脉冲（ARFI）是一种新开发的弹性成像技术，它利用声辐射力为传统超声检查提供额外的硬度信息。提出了一种计算机辅助诊断（CAD）系统，用于自动确定ARFI图像中的肿瘤边界并量化统计硬度信息，以减少对用户的依赖。水平集分割用于描绘B模式图像中的肿瘤边界，然后将分割后的边界映射到ARFI图像中的相应区域进行灰度计算。实验共评估了61个良性肿瘤和51个恶性肿瘤。基于所提出的ARFI特征的CAD系统的准确率为80%（90/112），灵敏度为80%（41/51），特异性为80%（49/61），显著优于定量B模式特征（p<0.05）。ARFI特征进一步与B模式特征（包括形状和纹理特征）相结合，以进一步提高性能（曲线下面积[AUC]，0.90对0.86）。总之，基于所提出的ARFI特征的CAD系统是一种有前途且高效的诊断方法。
