We present DD-hiODT, a novel deep-learning framework for fast 3D cell imaging. Our approach combines low-coherence holographic phase measurements with a neural network to eliminate complex scanning hardware. We successfully demonstrate rapid, high-fidelity reconstructions of red blood cells in under 600 milliseconds. New paper by ing. Michálková is available here.
