deep learningbased color holographic microscopy we report a framework based on a generative adversarial network that performs highfidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths the trained network learns to eliminate missingphaserelated artifacts and generates an accurate color transformation for the reconstructed image our framework is experimentally demonstrated using lung and prostate tissue sections that are labeled with different histological stains this framework is envisaged to be applicable to pointofcare histopathology and presents a significant improvement in the throughput of coherent microscopy systems given that only a single hologram of the specimen is required for accurate color imaging