Fig. 2
From: Assessing microscope image focus quality with deep learning
a Neural network model architecture; a probability distribution over 11 discrete focus classes is predicted for each input 84 × 84 image patch. This distribution can be summarized (see text) with two scalar values, the predicted defocus level and certainty of that prediction. b Example image annotated with patch-level predictions. The patch outlines have one of 11 hues denoting the predicted defocus level and increasing lightness denoting increased certainty. Defocus level ranges from in-focus to out-of-focus with an approximate blur diameter of 30 pixels. c A scatter plot of mean versus aggregate certainty, where each point corresponds to one Hoechst stain image of Human MCF-7 cells in the BBBC021 dataset [12], with hue denoting the predicted defocus level as in (b). d Example images from the circled regions are shown with patch-level annotations ordered from top to bottom. Scale bar is 20 μm or 60 pixels. Images in (d) share same color legend as (b). Transparency of points in (c) varies with number of images