3D reconstruction for ultrasonic C-scan images of tissue-mimicking phantom based on an improved K-nearest neighbor filtering

3D reconstruction for ultrasonic C-scan images of tissue-mimicking phantom based on an improved K-nearest neighbor filtering
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基于改进的 K 最近邻滤波的仿组织体模超声 C 扫描图像的 3D 重建

DOI:
10.1007/s11042-019-7686-1
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发表时间:
2019-05
影响因子:
3.6
通讯作者:
Wang Guanghui
Wang Guanghui
中科院分区:
计算机科学4区
文献类型:
--
作者:
Zhu Haijiang;Yang Tengfei;Yang Ping;He Longbiao;Wang Guanghui

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Although the ultrasonic C-scan technique has been extensively applied in nondestructive testing (NDT) in recent years, 3D reconstruction from ultrasonic C-scan images has not been well addressed. This paper develops a novel and efficient 3D reconstruction technique based on an improved K-nearest neighbor filtering for ultrasonic C-scan data of the tissue-mimicking phantoms. An edge-points-predicting approach based on K-nearest neighbor filtering is first proposed to predict the undetected edge points and to reduce the noise points for 2D ultrasonic images. Then, the 3D model is reconstructed from the clean edges by utilizing the surface rendering algorithm. The proposed approach is validated using the ultrasonic C-scan data of a liver model embedded in a tissue-mimicking phantom. The comparisons with other methods are presented in the experiments. The results demonstrate the effectiveness and the significantly improved reconstruction results of the proposed approach.
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