基于信噪比正则化局部荧光校正的血氧饱和度估计的改进。
Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.
出版信息
IEEE Trans Med Imaging. 2019 Feb;38(2):561-571. doi: 10.1109/TMI.2018.2867602. Epub 2018 Sep 10.
As photoacoustic (PA) imaging makes its way into the clinic, the accuracy of PA-based metrics becomes increasingly important. To address this need, a method combining finite-element-based local fluence correction (LFC) with signal-to-noise-ratio (SNR) regularization was developed and validated to accurately estimate oxygen saturation (SO) in tissue. With data from a Vevo LAZR system, performance of our LFC approach was assessed in ex vivo blood targets (37.6%-99.6% SO) and in vivo rat arteries. Estimation error of absolute SO and change in SO reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while the accuracy of the LFC method was correlated with the number of wavelengths acquired. This paper demonstrates the need for an SNR-regularized LFC to accurately quantify SO with PA imaging.
随着光声(PA)成像进入临床应用,基于 PA 的各项指标的准确性变得越来越重要。为了满足这一需求,开发并验证了一种结合基于有限元的局部辐照度校正(LFC)和信噪比(SNR)正则化的方法,以准确估计组织中的氧饱和度(SO)。使用 Vevo LAZR 系统的数据,在离体血液靶标(37.6%-99.6% SO)和体内大鼠动脉中评估了我们的 LFC 方法的性能。在没有 LFC 的情况下,绝对 SO 的估计误差和 SO 的变化分别从 10.1%和 6.4%降低到 2.8%和 2.0%,而 LFC 方法的准确性与采集的波长数相关。本文证明了需要 SNR 正则化的 LFC 来准确量化 PA 成像中的 SO。