CHARACTERIZING AND CORRECTING IMAGE DISTORTIONS ON THE TECNAI MICROSCOPES

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 自从开始在Tecnai显微镜上获取数据以来，我们一直担心图像失真会影响断层重建的质量。 对于来自Gatan成像滤波器（GIF）的图像，该问题尤其严重，因为在GIF和使用GIF所需的低放大率透镜模式中引起的失真。 我们开发了一个程序来解决的图像失真场从一组对重叠的图像的样品在两个阶段的位置。 一对的两个图像应该重叠约55%，并且必须获得四个不同方向的图像对。 我们的数据采集程序SerialEM具有轻松采集这些对的例程，因此现在可以直接采集此类数据并计算图像失真场。 另一种失真发生在倾斜的标本上，因为它位于一个梯度中，其中放大率和图像旋转随Z高度而变化。 这种梯度的效果显示突出时，蒙太奇是采取重叠图像的倾斜标本。 在尝试将帧移位到寄存器中时存在大量错误;当校正梯度失真时，错误被消除。 通过在两个不同的Z高度处拍摄样品的图像并确定它们之间的尺寸变化和旋转，可以容易地测量梯度。 梯度仅取决于光束强度，因此通过在每个倾斜系列期间记录光束强度，可以针对该梯度校正图像。 这两种梯度的校正已被纳入我们的标准层析成像处理流程中，因此用户很容易应用。 到目前为止，已经发现对GIF图像失真场的校正实质上改进了图像对准，而对梯度的校正给出了不显著的改进。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. Since starting to acquire data on our Tecnai microscopes, we have been concerned about image distortions impairing the quality of our tomographic reconstructions. The problem is particularly severe with images from the Gatan Imaging Filter (GIF), because of distortions induced in both the GIF and the low magnification lens mode needed to use the GIF. We developed a program to solve for the image distortion field from a set of pairs of overlapping images of a specimen at two stage positions. The two images of a pair should overlap by about 55%, and pairs at four distinct orientations must be obtained. Our data acquisition program, SerialEM, has a routine to acquire these pairs easily, so it is now straightforward to acquire such data and compute an image distortion field. Another kind of distortion occurs with a tilted specimen, because it is sitting in a gradient in which magnification and image rotation vary with Z height. The effect of this gradient shows up prominently when a montage is taken of overlapping images of a tilted specimen. There are substantial errors when trying to shift the frames into register; the errors are eliminated when gradient distortions are corrected for. The gradient can be measured easily by taking images with the specimen at two different Z heights and determining the size change and rotation between them. The gradient depends only on beam intensity, so by recording beam intensity during each tilt series it is possible to correct images for this gradient. Corrections for both kinds of gradients have been incorporated into our standard processing stream for tomography, so they are easy for users to apply. So far, correcting for the GIF image distortion field has been found to improve image alignment substantially, while correcting for the gradients has given insignificant improvements.