IEEE Trans Med Imaging. 2016 Dec;35(12):2546-2557. doi: 10.1109/TMI.2016.2584120. Epub 2016 Jun 23.
The computation of model matrix in the iterative imaging reconstruction process is crucial for the quantitative photoacoustic tomography (PAT). However, it is challenging to establish an outstanding model matrix to improve the overall imaging quality in PAT due to the noisy signal acquisition and inevitable artifacts. In this work, we present a novel method, named as the curve-driven-based model-matrix inversion (CDMMI), to calculate the model matrix for tomographic reconstruction in photoacoustic imaging. It eliminated the use of interpolation techniques, and thus avoided all interpolation related errors. The conventional interpolated-matrix-model inversion (IMMI) method was applied to evaluate its performance in numerical simulation, tissue-mimicking phantom and in vivo small animal studies. Results demonstrated that CDMMI achieved better reconstruction accuracy until IMMI kept increasing discrete points to 10000. Furthermore, the proposed method can suppress the negative influence of noise and artifacts effectively, which benefited the overall imaging quality of photoacoustic tomography.
在迭代成像重建过程中，模型矩阵的计算对于定量光声断层扫描（PAT）至关重要。然而，由于噪声信号采集和不可避免的伪影，很难建立一个出色的模型矩阵来提高 PAT 的整体成像质量。在这项工作中，我们提出了一种新的方法，称为基于曲线驱动的模型矩阵反演（CDMMI），用于计算光声成像中的层析重建模型矩阵。它消除了对插值技术的使用，从而避免了所有与插值相关的误差。传统的插值矩阵模型反演（IMMI）方法被应用于数值模拟、组织模拟体模和体内小动物研究中，以评估其性能。结果表明，直到 IMMI 不断增加离散点到 10000，CDMMI 才实现了更好的重建准确性。此外，该方法可以有效地抑制噪声和伪影的负面影响，从而有益于光声断层扫描的整体成像质量。
