Practical fluorescence reconstruction microscopy for large samples and low-magnification imaging
Fig 3
Cell-cell junction reconstruction from DIC data and capturing otherwise invisible morphology.
(A-D) Images of MDCK WT cells at 20x magnification were processed using a neural network trained to reconstruct cell-cell E-cadherin junctions. Representative ground truth features are shown alongside, and merged with, network predictions. The scale bar is 30 μm. (E) Ensemble statistics for E-cadherin reconstruction; N = 4539 test images, see S1 Table. (F) Line sections from identical spatial regions in (B) and (C) highlight the accuracy of predicted fluorescence intensity across cell-cell junctions (normalized to 16-bit histogram). From 2D transmitted light input (A), 3D structures may be detected. (G, H) Representative cell-cell junction and corresponding confocal section, highlighting the relationship between 2D junction signal and 3D features. ‘*’ in (G) is 7 μm above the basal plane. (I) Practical metric assessing estimated cell areas for entire E-cadherin training set (~30,000 individual cells). Junction segmentation was used to calculate cell areas for ground truth and FRM predictions and the distributions of detected cell areas were plotted for comparison. Ground truth mean area was 1813 pix2; FRM predicted mean area was 1791 pix2.