Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.
Improved Photoacoustic-Based Oxygen Saturation Estimation With SNR-Regularized Local Fluence Correction.
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DOI：
10.1109/tmi.2018.2867602
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发表时间：
2019-03
影响因子：
10.6
通讯作者：
Bouchard RR
中科院分区：
文献类型：
--
作者：
Naser MA;Sampaio DRT;Munoz NM;Wood CA;Mitcham TM;Stefan W;Sokolov KV;Pavan TZ;Avritscher R;Bouchard RR
随着光声（PA）成像进入临床，基于PA的指标的准确性变得越来越重要。为了满足这一需求，开发并验证了一种将基于有限元的局部注量校正（LFC）与信噪比（SNR）正则化相结合的方法，以准确估计组织中的氧饱和度（SO2）。使用来自Vevo LAZR系统的数据，在离体血液目标（37.6% -99.6%SO2）和体内大鼠动脉中评估了我们的LFC方法的性能。绝对SO2和SO2的变化的估计误差分别从10.1%和6.4%，没有LFC减少到2.8%和2.0%，分别与LFC，而LFC方法的准确性与获得的波长数相关。这项工作证明了SNR正则化LFC的需要，以准确地量化SO2与PA成像。
As photoacoustic (PA) imaging makes its way into the clinic, 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 (SO2) 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% SO2) and in vivo rat arteries. Estimation error of absolute SO2 and change in SO2 reduced from 10.1% and 6.4%, respectively, without LFC to 2.8% and 2.0%, respectively, with LFC, while accuracy of the LFC method was correlated with the number of wavelengths acquired. This work demonstrates the need for SNR-regularized LFC to accurately quantify SO2 with PA imaging.