State Key Laboratory of Modern Optical Instrumentation, Department of Optical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.
PLoS One. 2013 Sep 13;8(9):e73093. doi: 10.1371/journal.pone.0073093. eCollection 2013.
The purpose of ultrasound elastography is to identify lesions by reconstructing the hardness characteristics of tissue reconstructed from ultrasound data. Conventional quasi-static ultrasound elastography is easily applied to obtain axial strain components along the compression direction, with the results inverted to represent the distribution of tissue hardness under the assumption of constant internal stresses. However, previous works of quasi-static ultrasound elastography have found it difficult to obtain the lateral and shear strain components, due to the poor lateral resolution of conventional ultrasound probes. The physical nature of the strain field is a continuous vector field, which should be fully described by the axial, lateral, and shear strain components, and the clinical value of lateral and shear strain components of deformed tissue is gradually being recognized by both engineers and clinicians. Therefore, a biomechanical-model-constrained filtering framework is proposed here for recovering a full displacement field at a high spatial resolution from the noisy ultrasound data. In our implementation, after the biomechanical model constraint is integrated into the state-space equation, both the axial and lateral displacement components can be recovered at a high spatial resolution from the noisy displacement measurements using a robust H∞ filter, which only requires knowledge of the worst-case noise levels in the measurements. All of the strain components can then be calculated by applying a gradient operator to the recovered displacement field. Numerical experiments on synthetic data demonstrated the robustness and effectiveness of our approach, and experiments on phantom data and in-vivo clinical data also produced satisfying results.
超声弹性成像是通过从超声数据中重建组织的硬度特性来识别病变。传统的准静态超声弹性成像很容易应用于获得沿压缩方向的轴向应变分量,结果被反转以表示在假设恒定内部应力下组织硬度的分布。然而,由于传统超声探头的横向分辨率较差,以前的准静态超声弹性成像工作发现很难获得横向和剪切应变分量。应变场的物理性质是一个连续的向量场,应该通过轴向、横向和剪切应变分量来充分描述,变形组织的横向和剪切应变分量的临床价值正逐渐被工程师和临床医生所认识。因此,这里提出了一种基于生物力学模型约束的滤波框架,用于从噪声超声数据中以高空间分辨率恢复完整的位移场。在我们的实现中,在将生物力学模型约束集成到状态空间方程之后,使用鲁棒 H∞滤波器可以从噪声位移测量中以高空间分辨率恢复轴向和横向位移分量,该滤波器仅需要知道测量中最坏情况的噪声水平。然后可以通过对恢复的位移场应用梯度算子来计算所有应变分量。对合成数据的数值实验证明了我们方法的稳健性和有效性,对体模数据和体内临床数据的实验也产生了令人满意的结果。