Fast particle characterization using digital holography and neural networks

We propose using a neural network approach in conjunction with digital holographic microscopy in order to rapidly determine relevant parameters such as the core and shell diameter of coated, non-absorbing spheres. We do so without requiring a time-consuming reconstruction of the cell image. In contrast to previous approaches, we are able to obtain a continuous value for parameters such as size, as opposed to binning into a discrete number of categories. Also, we are able to separately determine both core and shell diameter. For simulated particle sizes ranging between 7 and 20 μm, we obtain accuracies of (4.4±0.2)% and (0.74±0.01)% for the core and shell diameter, respectively.