IEEE Trans Med Imaging. 2022 Jan;41(1):103-120. doi: 10.1109/TMI.2021.3104521. Epub 2021 Dec 30.
Photoacoustic microscopy (PAM) leverages the optical absorption contrast of blood hemoglobin for high-resolution, multi-parametric imaging of the microvasculature in vivo. However, to quantify the blood flow speed, dense spatial sampling is required to assess blood flow-induced loss of correlation of sequentially acquired A-line signals, resulting in increased laser pulse repetition rate and consequently optical fluence. To address this issue, we have developed a sparse modeling approach for blood flow quantification based on downsampled PAM data. Evaluation of its performance both in vitro and in vivo shows that this sparse modeling method can accurately recover the substantially downsampled data (up to 8 times) for correlation-based blood flow analysis, with a relative error of 12.7 ± 6.1 % across 10 datasets in vitro and 12.7 ± 12.1 % in vivo for data downsampled 8 times. Reconstruction with the proposed method is on par with recovery using compressive sensing, which exhibits an error of 12.0 ± 7.9 % in vitro and 33.86 ± 26.18 % in vivo for data downsampled 8 times. Both methods outperform bicubic interpolation, which shows an error of 15.95 ± 9.85 % in vitro and 110.7 ± 87.1 % in vivo for data downsampled 8 times.
光声显微镜 (PAM) 利用血液血红蛋白的光吸收对比，实现了活体微血管的高分辨率、多参数成像。然而，为了量化血流速度，需要进行密集的空间采样，以评估血流诱导的顺序获取的 A 线信号相关性的损失，从而导致激光脉冲重复率增加，进而导致光通量增加。为了解决这个问题，我们开发了一种基于稀疏建模的血流定量方法，用于处理 PAM 数据。在体外和体内的性能评估表明，这种稀疏建模方法可以准确地恢复基于相关性的血流分析的大幅下采样数据（高达 8 倍），在 10 个体外数据集和 8 倍下采样的 12.7 ± 12.1%的体内数据中，相对误差为 12.7 ± 6.1%。与使用压缩感知的重建相比，该方法的恢复效果相当，在 8 倍下采样的体外数据中误差为 12.0 ± 7.9%，体内数据中误差为 33.86 ± 26.18%。这两种方法都优于双三次插值，在 8 倍下采样的体外数据中误差为 15.95 ± 9.85%，体内数据中误差为 110.7 ± 87.1%。
