Fig. 5: Artificial labelling of E. coli membranes.
From: DeepBacs for multi-task bacterial image analysis using open-source deep learning approaches
a fnet and CARE predictions of diffraction-limited (i) and PAINT super-resolution (SR) (ii) membrane labels obtained from bright field (BF) images. GT = ground truth. Values represent averages from five test images and the respective standard deviation b Pseudo-dual-colour images of drug-treated E. coli cells. Nucleoids were super-resolved using PAINT imaging with JF646-Hoechst64. Membranes were predicted using the trained fnet model. CAM = Chloramphenicol. Scale bars are 2 µm (a) and 1 µm (b).
