Wang Jin, Zhang Chen, Wang Yuanyuan
Department of Electronic Engineering, Fudan University, Shanghai, 200433, China.
Key Laboratory of Medical Imaging Computing and Computer-Assisted Intervention of Shanghai, Shanghai, 200433, China.
Biomed Eng Online. 2017 May 30;16(1):64. doi: 10.1186/s12938-017-0366-3.
In photoacoustic tomography (PAT), total variation (TV) based iteration algorithm is reported to have a good performance in PAT image reconstruction. However, classical TV based algorithm fails to preserve the edges and texture details of the image because it is not sensitive to the direction of the image. Therefore, it is of great significance to develop a new PAT reconstruction algorithm to effectively solve the drawback of TV.
In this paper, a directional total variation with adaptive directivity (DDTV) model-based PAT image reconstruction algorithm, which weightedly sums the image gradients based on the spatially varying directivity pattern of the image is proposed to overcome the shortcomings of TV. The orientation field of the image is adaptively estimated through a gradient-based approach. The image gradients are weighted at every pixel based on both its anisotropic direction and another parameter, which evaluates the estimated orientation field reliability. An efficient algorithm is derived to solve the iteration problem associated with DDTV and possessing directivity of the image adaptively updated for each iteration step.
Several texture images with various directivity patterns are chosen as the phantoms for the numerical simulations. The 180-, 90- and 30-view circular scans are conducted. Results obtained show that the DDTV-based PAT reconstructed algorithm outperforms the filtered back-projection method (FBP) and TV algorithms in the quality of reconstructed images with the peak signal-to-noise rations (PSNR) exceeding those of TV and FBP by about 10 and 18 dB, respectively, for all cases. The Shepp-Logan phantom is studied with further discussion of multimode scanning, convergence speed, robustness and universality aspects. In-vitro experiments are performed for both the sparse-view circular scanning and linear scanning. The results further prove the effectiveness of the DDTV, which shows better results than that of the TV with sharper image edges and clearer texture details. Both numerical simulation and in vitro experiments confirm that the DDTV provides a significant quality improvement of PAT reconstructed images for various directivity patterns.
在光声断层成像（PAT）中，据报道基于总变差（TV）的迭代算法在PAT图像重建中具有良好性能。然而，传统的基于TV的算法由于对图像方向不敏感，无法保留图像的边缘和纹理细节。因此，开发一种新的PAT重建算法以有效解决TV的缺点具有重要意义。
本文提出了一种基于具有自适应方向性的方向总变差（DDTV）模型的PAT图像重建算法，该算法基于图像的空间变化方向性模式对图像梯度进行加权求和，以克服TV的缺点。通过基于梯度的方法自适应估计图像的方向场。基于各像素的各向异性方向和另一个评估估计方向场可靠性的参数对图像梯度进行加权。推导了一种高效算法来解决与DDTV相关的迭代问题，并为每个迭代步骤自适应更新具有图像方向性。
选择几个具有不同方向性模式的纹理图像作为数值模拟的体模。进行了180视图、90视图和30视图的圆形扫描。获得的结果表明，基于DDTV的PAT重建算法在重建图像质量方面优于滤波反投影法（FBP）和TV算法，在所有情况下，峰值信噪比（PSNR）分别比TV和FBP高出约10 dB和18 dB。对Shepp-Logan体模进行了研究，并进一步讨论了多模式扫描、收敛速度、鲁棒性和通用性等方面。对稀疏视图圆形扫描和线性扫描都进行了体外实验。结果进一步证明了DDTV的有效性，其显示出比TV更好的结果，图像边缘更清晰，纹理细节更清楚。数值模拟和体外实验均证实，DDTV显著提高了各种方向性模式的PAT重建图像的质量。
