Zheng Sun, Yingsa Hou, Meichen Sun, Qi Meng
Department of Electronic and Communication Engineering, North China Electric Power University, Baoding 071003, Hebei, People's Republic of China.
Hebei Key Laboratory of Power Internet of Things Technology, North China Electric Power University, Baoding 071003, Hebei, People's Republic of China.
Phys Med Biol. 2023 Mar 20;68(6). doi: 10.1088/1361-6560/acbe90.
. Photoacoustic tomography (PAT) is a rapidly evolving imaging modality that provides images with high contrast and spatial resolution showing the optical properties of biological tissues. The photoacoustic pressure is proportional to the product of the optical absorption coefficient and the local light fluence. The essential challenge in reconstructing quantitative images representing spatially varying absorption coefficients is the unknown light fluence. In addition, optical attenuation induces spatial variations in the light fluence, and the heterogeneity of the fluence determines the limits of reconstruction quality and depth.In this work, a reconstruction enhancement scheme is proposed to compensate for the variation in the light fluence in the absorption coefficient recovery. The inverse problem of the radiance Monte Carlo model describing light transport through the tissue is solved by using an alternating optimization strategy. In the iteration, the absorption coefficients and photon weights are alternately updated.The method provides highly accurate quantitative images of absorption coefficients in simulations, phantoms, andstudies. The results show that the method has great potential for improving the accuracy of absorption coefficient recovery compared to conventional reconstruction methods that ignore light fluence variations. Comparison with state-of-the-art fluence compensation methods shows significant improvements in root mean square error, normalized mean square absolute distance, and structural similarity metrics.This method achieves high precision quantitative imaging by compensating for nonuniform light fluence without increasing the complexity and operation of the imaging system.
光声断层扫描（PAT）是一种快速发展的成像方式，它能提供具有高对比度和空间分辨率的图像，展示生物组织的光学特性。光声压力与光吸收系数和局部光通量的乘积成正比。在重建表示空间变化吸收系数的定量图像时，关键挑战在于未知的光通量。此外，光学衰减会引起光通量的空间变化，而光通量的不均匀性决定了重建质量和深度的限制。在这项工作中，提出了一种重建增强方案，以补偿吸收系数恢复过程中光通量的变化。通过使用交替优化策略解决了描述光在组织中传输的辐射度蒙特卡罗模型的逆问题。在迭代过程中，吸收系数和光子权重交替更新。该方法在模拟、体模和研究中提供了高度准确的吸收系数定量图像。结果表明，与忽略光通量变化的传统重建方法相比，该方法在提高吸收系数恢复精度方面具有巨大潜力。与最先进的光通量补偿方法相比，在均方根误差、归一化均方绝对距离和结构相似性指标方面有显著改进。该方法通过补偿不均匀光通量实现了高精度定量成像，而无需增加成像系统的复杂性和操作。
