Fig. 4From: Assessing microscope image focus quality with deep learningPrediction of absolute focus quality on training data cell type (U2OS cells), Hoechst stain with varying image brightness and background by applying a multiplicative gain and additive offset (16-bit range) to test images. Confusion matrices show the image counts for all pairs of predicted and actual focus levels, where images in each class are separated by a blur diameter of 3 pixels (px). In the absence of a gain or offset (first column), both models perform similarly, but the model trained without data augmentation (first row) is biased toward predicting brighter images as more in-focus, and fails to separate defocus levels entirely with a large offset appliedBack to article page