Beijing Engineering Research Center of Mixed Reality and Advanced Display, School of Optics and Electronics, Beijing Institute of Technology, Beijing, 100081, China.
School of Computer Science and Engineering, Beihang University, Beijing, 100191, China.
Biomed Eng Online. 2017 Oct 30;16(1):124. doi: 10.1186/s12938-017-0411-2.
3D ultrasound volume reconstruction from B-model ultrasound slices can provide more clearly and intuitive structure of tissue and lesion for the clinician.
This paper proposes a novel Global Path Matching method for the 3D reconstruction of freehand ultrasound images. The proposed method composes of two main steps: bin-filling scheme and hole-filling strategy. For the bin-filling scheme, this study introduces two operators, including the median absolute deviation and the inter-quartile range absolute deviation, to calculate the invariant features of each voxel in the 3D ultrasound volume. And the best contribution range for each voxel is obtained by calculating the Euclidian distance between current voxel and the voxel with the minimum invariant features. Hence, the intensity of the filling vacant voxel can be obtained by weighted combination of the intensity distribution of pixels in the best contribution range. For the hole-filling strategy, three conditions, including the confidence term, the data term and the gradient term, are designed to calculate the weighting coefficient of the matching patch of the vacant voxel. While the matching patch is obtained by finding patches with the best similarity measure that defined by the three conditions in the whole 3D volume data.
Compared with VNN, PNN, DW, FMM, BI and KR methods, the proposed Global Path Matching method can restore the 3D ultrasound volume with minimum difference.
Experimental results on phantom and clinical data sets demonstrate the effectiveness and robustness of the proposed method for the reconstruction of ultrasound volume.
从 B 型超声切片重建 3D 超声体积可以为临床医生提供更清晰、更直观的组织结构和病变。
本文提出了一种新的自由式超声图像 3D 重建全局路径匹配方法。该方法由两个主要步骤组成：-bin 填充方案和孔填充策略。对于 bin 填充方案，本研究引入了两个运算符，包括中位数绝对偏差和四分位距绝对偏差，以计算 3D 超声体积中每个体素的不变特征。通过计算当前体素与不变特征最小的体素之间的欧几里得距离，获得每个体素的最佳贡献范围。因此，可以通过加权组合最佳贡献范围内像素的强度分布来获得填充空缺体素的强度。对于孔填充策略，设计了三个条件，包括置信项、数据项和梯度项，以计算空缺体素的匹配补丁的加权系数。而匹配补丁是通过在整个 3D 体积数据中找到满足三个条件的最佳相似性度量的补丁来获得的。
与 VNN、PNN、DW、FMM、BI 和 KR 方法相比，所提出的全局路径匹配方法可以以最小的差异恢复 3D 超声体积。
在体模和临床数据集上的实验结果证明了该方法对超声体积重建的有效性和鲁棒性。
