  Computer-generated holography (CGH) has broad applications such as
direct-view display, virtual and augmented reality, as well as optical
microscopy. CGH usually utilizes a spatial light modulator that displays a
computer-generated phase mask, modulating the phase of coherent light in order
to generate customized patterns. The algorithm that computes the phase mask is
the core of CGH and is usually tailored to meet different applications. CGH for
optical microscopy usually requires 3D accessibility (i.e., generating
overlapping patterns along the $z$-axis) and micron-scale spatial precision.
Here, we propose a CGH algorithm using an unsupervised generative model
designed for optical microscopy to synthesize 3D selected illumination. The
algorithm, named sparse deep CGH, is able to generate sparsely distributed
points in a large 3D volume with higher contrast than conventional CGH
algorithms.
