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Fig. 9 | BMC Bioinformatics

Fig. 9

From: PIXER: an automated particle-selection method based on segmentation using a deep neural network

Fig. 9

Experiments on simulated data. (a) Example of micrographs including the original micrograph, heat map of probability, binarized segmentation results and final coordinates. (b) Detailed IOU results of 45 micrographs. (c) The IOU results of our method on the simulated data with different SNRs. Here the SNR is defined as \( SNR=10{\mathit{\log}}_{10}\left(\frac{\sum \limits_{x=0}^N\sum \limits_{y=0}^M\widehat{f}{\left(x,y\right)}^2}{\sum \limits_{x=0}^N\sum \limits_{y=0}^M{\left[f\left(x,y\right)-\widehat{f}\left(x,y\right)\right]}^2}\right) \), where \( \widehat{f}\left(x,y\right) \) is the signal of simulated data generated from InSilicoTEM with no noise, and f(x, y) is the simulated data with noise

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