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• W4384338633 abstract "Abstract The high detection efficiencies of direct electron detectors facilitate the routine collection of low fluence electron micrographs and diffraction patterns. Low dose and low fluence electron microscopy experiments are the only practical way to acquire useful data from beam sensitive pharmaceutical and biological materials. Appropriate modeling of low fluence images acquired using direct electron detectors is, therefore, paramount for quantitative analysis of the experimental images. We have developed a new open-source Python package to accurately model any single layer direct electron detector for low and high fluence imaging conditions, including a means to validate against experimental data through computation of modulation transfer function and detective quantum efficiency." @default.
• W4384338633 created "2023-07-15" @default.
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• W4384338633 date "2023-07-14" @default.
• W4384338633 modified "2023-09-27" @default.
• W4384338633 title "InFluence: An Open-Source Python Package to Model Images Captured with Direct Electron Detectors" @default.
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• W4384338633 doi "https://doi.org/10.1093/micmic/ozad064" @default.
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