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Fig. 13 | BMC Bioinformatics

Fig. 13

From: DeepCryoPicker: fully automated deep neural network for single protein particle picking in cryo-EM

Fig. 13

Fully automated good training top-view training particles-selection results using AutoCryoPicker [24] approach and diferenrt micrographs from Apoferritin [27] and KLH [26] datasets. a, e Individual top-view particle binary mask form the Apoferritin [27] and KLH [26] datasets. b, f CHT [24] perfect circle on top of the particle’s binary masks. c, g Generated perfect top-view binary mask based on the center and dimeter that are automatically extracted from the CHT [24] using picked top-view particles form Apoferritin [27] and KLH [26]. d, h The full automated good top-view training particle selection results based on the perfect mask generation using CHT [24] and different top-view picked particles from different datasets (Apoferritin [27] and KLH [26]). i, k, m, o Other examples of the top-view particle’s binary masks that the modified CHT [24] has failed to draw perfect circles on top of them (dash red lines illustrate the missing part of the particle’s background while the dash blue lines illustrate the missing part of the circular object). j, l, n, p The full automated bad top-view training particle selection using different top-view picked particles from different datasets (Apoferritin [27] and KLH [26]) (dash red lines illustrate the missing part of the particle’s background while the dash blue lines illustrate the missing part of the circular object)

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