PDF(Pubmed)
Abstract：
In surgery, the surgical smoke generated during tissue dissection and hemostasis can degrade the image quality, affecting tissue visibility and interfering with the further image processing. Developing reliable and interpretable computational imaging methods for restoring smoke-affected surgical images is crucial, as typical image restoration methods relying on color-texture information are insufficient. Here a computational polarization imaging method through surgical smoke is demonstrated, including a refined polarization difference estimation based on the discrete electric field direction, and a corresponding prior-based estimation method, for better parameter estimation and image restoration performance. Results and analyses for ex vivo, the first in vivo animal experiments, and human oral cavity tests show that the proposed method achieves visibility restoration and color recovery of higher quality, and exhibits good generalization across diverse imaging scenarios with interpretability. The method is expected to enhance the precision, safety, and efficiency of advanced image-guided and robotic surgery.
摘要：
在手术中，组织解剖和止血过程中产生的手术烟雾会降低图像质量，影响组织的可见性和干扰进一步的图像处理。开发可靠且可解释的计算成像方法来恢复受烟雾影响的手术图像至关重要，由于典型的图像恢复方法依赖于颜色纹理信息是不够的。这里演示了一种通过手术烟雾的计算偏振成像方法，包括基于离散电场方向的精细极化差估计，以及相应的基于先验的估计方法，更好的参数估计和图像复原性能。离体结果和分析，第一次体内动物实验，和人体口腔测试表明，该方法实现了更高质量的能见度恢复和颜色恢复，并在具有可解释性的不同成像场景中表现出良好的概括。该方法有望提高精密度,安全,先进的图像引导和机器人手术的效率。
