目的:聚焦离子束-扫描电子显微镜(FIB-SEM)可以在纳米级对细胞和组织进行三维超微结构分析。该技术用FIB迭代地去除样品的一部分,并从暴露的表面拍摄SEM图像。切片厚度通常高于图像像素大小,以减少采集时间,从而导致各向异性分辨率。在这项工作中,我们沿着切片方向探索新颖的插值方法,以产生各向同性分辨率,并促进FIB-SEM3D体积的正确解释。
方法:在这种情况下,通常在假设通过连续图像的变化相对平滑的情况下应用经典插值方法。然而,例如,样品中的结构的实际3D布置可以引起FIB-SEM堆叠的连续图像之间的生物特征的显著变化。我们已经开发了一种新颖的插值策略,该策略通过使用光流(OF)来估计这种变化。作为一个中间阶段,通过对准生物结构的空间区域来产生OF补偿图像。然后从这些OF补偿图像生成插值图像。通过将插值后的图像与各向异性堆叠的原始图像交错来组装最终的各向同性堆叠。
结果:使用基于皮尔逊相关系数(PCC)的客观评估和基于视觉结果的定性评估,比较了OF驱动和经典插值方法,使用公共数据集和代表性各向异性条件。客观评估表明,OF驱动插值总是产生更高的PCC值,插值图像更接近地面真相。定性评估证实了这些结果,并证实了经典插值可能使连续图像之间具有实质性变化的区域模糊,而OF驱动的插值提供了清晰度。
结论:我们开发了一种OF驱动的插值方法,用于从实验各向异性数据生成具有各向同性分辨率的FIB-SEM堆叠。它适应通过FIB-SEM堆叠的图像观察到的生物结构的快速变化。我们的方法优于经典插值,并在连续实验图像之间存在显着变化的情况下设法产生清晰的插值视图。
OBJECTIVE: Focused Ion Beam - Scanning Electron Microscopy (FIB-SEM) allows three-dimensional ultrastructural analysis of cells and tissues at the nanoscale. The technique iteratively removes a section of the sample with a FIB and takes an SEM image from the exposed surface. The section thickness is usually higher than the image pixel size to reduce acquisition time, thus resulting in anisotropic resolution. In this work, we explore novel interpolation methods along the sectioning direction to produce isotropic resolution and facilitate proper interpretation of the FIB-SEM 3D volumes.
METHODS: Classical interpolation methods are usually applied in this context under the assumption that the changes through successive images are relatively smooth. However, the actual 3D arrangement of the structures in the sample may cause significant changes in the biological features between consecutive images of the FIB-SEM stacks. We have developed a novel interpolation strategy that accounts for this variation by using the Optical Flow (OF) to estimate it. As an intermediate stage, OF-compensated images are produced by aligning the spatial regions of the biological structures. Interpolated images are then generated from these OF-compensated images. The final isotropic stack is assembled by interleaving the interpolated images with the original images of the anisotropic stack.
RESULTS: OF-driven and classical interpolation methods were compared using an objective assessment based on Pearson Correlation Coefficient (PCC) and a qualitative evaluation based on visual results, using public datasets and representative anisotropy conditions. The objective assessment demonstrated that the OF-driven interpolation always yields higher PCC values, with interpolated images closer to the ground truth. The qualitative evaluation corroborated those results and confirmed that classical interpolation may blur areas with substantial changes between consecutive images whereas OF-driven interpolation provides sharpness.
CONCLUSIONS: We have developed an OF-driven interpolation approach to generating FIB-SEM stacks with isotropic resolution from experimental anisotropic data. It adapts to the rapid variation of the biological structures observed through the images of the FIB-SEM stack. Our approach outperforms classical interpolation and manages to produce sharp interpolated views in cases where there are significant changes between consecutive experimental images.