Bhamre Tejal, Zhao Zhizhen, Singer Amit
Dept. of Physics, Princeton University.
Dept. of Electrical Engineering, UIUC.
Proc IEEE Int Symp Biomed Imaging. 2017 Apr;2017:654-658. doi: 10.1109/ISBI.2017.7950605. Epub 2017 Jun 19.
Single particle reconstruction (SPR) from cryo-electron microscopy (EM) is a technique in which the 3D structure of a molecule needs to be determined from its contrast transfer function (CTF) affected, noisy 2D projection images taken at unknown viewing directions. One of the main challenges in cryo-EM is the typically low signal to noise ratio (SNR) of the acquired images. 2D classification of images, followed by class averaging, improves the SNR of the resulting averages, and is used for selecting particles from micrographs and for inspecting the particle images. We introduce a new affinity measure, akin to the Mahalanobis distance, to compare cryo-EM images belonging to different defocus groups. The new similarity measure is employed to detect similar images, thereby leading to an improved algorithm for class averaging. We evaluate the performance of the proposed class averaging procedure on synthetic datasets, obtaining state of the art classification.
基于冷冻电子显微镜（EM）的单颗粒重建（SPR）是一种从受对比度传递函数（CTF）影响、在未知观察方向下拍摄的有噪声的二维投影图像中确定分子三维结构的技术。冷冻电镜的主要挑战之一是所采集图像的信噪比（SNR）通常较低。对图像进行二维分类，然后进行类平均，可以提高所得平均图像的信噪比，并用于从显微照片中选择颗粒以及检查颗粒图像。我们引入了一种类似于马氏距离的新亲和度度量，用于比较属于不同散焦组的冷冻电镜图像。这种新的相似性度量用于检测相似图像，从而得到一种改进的类平均算法。我们在合成数据集上评估了所提出的类平均程序的性能，获得了当前最优的分类结果。
