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Evaluation of automated particle picking for cryogenic electron microscopy using high‐precision transmission electron microscope simulation based on a multi‐slice method
Author(s) -
Ohashi Masataka,
Hosokawa Fumio,
Shinkawa Takao,
Iwasaki Kenji
Publication year - 2021
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s2059798321005106
Subject(s) - transmission electron microscopy , particle (ecology) , orientation (vector space) , software , electron microscope , computer science , materials science , microscope , electron , optics , artificial intelligence , nanotechnology , physics , geology , quantum mechanics , oceanography , geometry , mathematics , programming language
This work describes the GRIPS automated particle‐picking software for cryogenic electron microscopy and the evaluation of this software using elbis , a high‐precision transmission electron microscope (TEM) image simulator. The goal was to develop a method that can pick particles under a small defocus condition where the particles are not clearly visible or under a condition where the particles are exhibiting preferred orientation. The proposed method handles these issues by repeatedly performing three processes, namely extraction, two‐dimensional classification and positioning, and by introducing mask processing to exclude areas with particles that have already been picked. TEM images for evaluation were generated with a high‐precision TEM image simulator. TEM images containing both particles and amorphous ice were simulated by randomly placing O atoms in the specimen. The experimental results indicate that the proposed method can be used to pick particles correctly under a relatively small defocus condition. Moreover, the results show that the mask processing introduced in the proposed method is valid for particles exhibiting preferred orientation. It is further shown that the proposed method is applicable to data collected from real samples.

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