Deep learning for faster holographic reconstruction processing in microfluidics

Abstract

The huge amount of phase maps to be numerically retrieved from digital holograms is the actual bottleneck of the high-throughput holographic flow cytometry. An end-to-end neural network is discussed to speed up the holographic processing.