Sparse deep computer-generated holography for optical microscopy
This work addresses the need for precise 3D optical microscopy illumination, though it appears incremental as it builds on existing CGH approaches.
The paper tackled the problem of generating 3D illumination patterns in optical microscopy using computer-generated holography, resulting in a new algorithm that produces sparsely distributed points with higher contrast than conventional methods.
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.