Fig. 3
From: A machine learning approach for online automated optimization of super-resolution optical microscopy
Multi-objective live-cell optimization of GFP imaging. a Parameter configurations selected by Kernel TS during different imaging trials in three different cell types: neurons (green), PC12 (blue), and HEK293 (orange). b Cumulative regret curve of (left) image quality alone (images with a quality score below 60%) and (right) image quality and photobleaching (images with a quality score below 60% or photobleaching above 75%). c Example images obtained among the last ten images of one optimization sequence for each cell type. The confocal image was taken before two consecutive STED images (labeled as STED-1 and STED-2). Note the differences in intensity scales across images to reflect differences in fluorescence intensity (confocal images) or photobleaching (STED1 vs. STED2). Scale bar 1 μm
