Abstract
Cryogenic Electron Microscopy (Cryo-EM) has been established as one of the key players in Structural Biology. It can reconstruct a 3D model of the sample at the near-atomic resolution, which led to a Method of the year award by Nature, and the Nobel Prize in 2017. With the growing number of facilities, faster microscopes, and new imaging techniques, new algorithms are needed to process the so-called movies data produced by the microscopes in real-time, while preserving a high resolution and maximum of additional information. In this article, we present a new algorithm used for movie alignment, called FlexAlign. FlexAlign is able to correctly compensate for the shift produced during the movie acquisition on-the-fly, using the current generation of hardware. The algorithm performs a global and elastic local registration of the movie frames using Cross-Correlation and B-spline interpolation for high precision. We show that our execution time is compatible with real-time correction and that we preserve the high-resolution information up to high frequency.
Highlights
The processing pipeline of the Cryogenic Electron Microscopy (Cryo-EM) consists of several steps, movie alignment being the very first one
A micrograph is produced, which is later used for particle picking, Contrast Transfer Function (CTF) estimation, and other steps of the image processing pipeline
FlexAlign produces high contrast micrographs, it is rather robust to noise, and it is able to process movies at the microscope acquisition speed, using the current generation of the Graphical Processing Unit (GPU)
Summary
The processing pipeline of the Cryo-EM consists of several steps, movie alignment being the very first one. The aim of the local alignment is to compensate for more complex movements of the particles, should they be caused by the beam, doming, or another cause It works on a divide and conquer basis—the movie is divided into small patches, and the alignment is solved independently for each patch. FlexAlign produces high contrast micrographs, it is rather robust to noise, and it is able to process movies at the microscope acquisition speed, using the current generation of the GPUs. The rest of the paper is organized as follows. While MotionCor provides good performance and precision, it is not providing, to the best of our knowledge, the data needed for particle tracking It allows for both global and local alignment and is accelerated on GPU. The goal of FlexAlign is to combine the best of these, namely, the short computational time, the flexibility of elastic deformations, support for detailed pixel tracking, and open-source implementation
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