Wang Daqian, Qi Ji, Huang Baoru, Noble Elizabeth, Stoyanov Danail, Gao Jun, Elson Daniel S
School of Computer and Information, Hefei University of Technology, Hefei, 230601, China.
Hamlyn Centre for Robotic Surgery, Imperial College London, London, SW7 2AZ, UK.
Biomed Opt Express. 2022 Mar 22;13(4):2364-2379. doi: 10.1364/BOE.451517. eCollection 2022 Apr 1.
Smoke generated during surgery affects tissue visibility and degrades image quality, affecting surgical decisions and limiting further image processing and analysis. Polarization is a fundamental property of light and polarization-resolved imaging has been studied and applied to general visibility restoration scenarios such as for smog or mist removal or in underwater environments. However, there is no related research or application for surgical smoke removal. Due to differences between surgical smoke and general haze scenarios, we propose an alternative imaging degradation model by redefining the form of the transmission parameters. The analysis of the propagation of polarized light interacting with the mixed medium of smoke and tissue is proposed to realize polarization-based smoke removal (visibility restoration). Theoretical analysis and observation of experimental data shows that the cross-polarized channel data generated by multiple scattering is less affected by smoke compared to the co-polarized channel. The polarization difference calculation for different color channels can estimate the model transmission parameters and reconstruct the image with restored visibility. Qualitative and quantitative comparison with alternative methods show that the polarization-based image smoke-removal method can effectively reduce the degradation of biomedical images caused by surgical smoke and partially restore the original degree of polarization of the samples.
手术过程中产生的烟雾会影响组织的可见性并降低图像质量，进而影响手术决策，并限制进一步的图像处理和分析。偏振是光的一种基本属性，偏振分辨成像已得到研究，并应用于一般的能见度恢复场景，如去除烟雾或雾气，或在水下环境中。然而，目前尚无关于去除手术烟雾的相关研究或应用。由于手术烟雾与一般雾霾场景存在差异，我们通过重新定义传输参数的形式，提出了一种替代性的成像退化模型。提出了对偏振光与烟雾和组织混合介质相互作用的传播进行分析，以实现基于偏振的烟雾去除（能见度恢复）。理论分析和实验数据观察表明，与共偏振通道相比，多次散射产生的交叉偏振通道数据受烟雾的影响较小。对不同颜色通道进行偏振差异计算，可以估计模型传输参数，并重建能见度恢复的图像。与其他方法的定性和定量比较表明，基于偏振的图像烟雾去除方法可以有效减少手术烟雾对生物医学图像的退化，并部分恢复样本的原始偏振度。
