In-line holographic microscopy with model-based analysis

An in-line holographic microscope is an optical microscope outfitted with a coherent light source, such as a laser. Light scattered by the specimen interferes with the transmitted beam, and the intensity of that interference pattern constitutes a hologram. Unlike a conventional photograph, a hologram contains information about the phase of the scattered light that is useful for measuring the composition and 3D arrangement of microscopic objects in the specimen. This Primer presents an overview of experimental methods and discusses three recent analysis techniques: fitting scattering models to the hologram; using machine learning to localize and classify the specimen; and a hybrid approach that uses machine learning to initialize fits. The combination of holographic microscopy and model-based analysis is well suited to applications where precise, quantitative results are needed with high acquisition speed. Such applications include studying properties of heterogeneous colloidal dispersions, measuring colloidal interactions, monitoring stresses in soft materials, detecting molecular binding and aggregation, and following the motion of microorganisms in three dimensions. We discuss the reproducibility and current limitations of each method. Finally, we anticipate directions for future development and provide an outlook on the integration between experiment and computational analysis, an emerging paradigm for microscopy.