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How Interactive Visualization Led to Insights in Digital Holographic Microscopy

Summary

Digital holographic microscopy is a fast 3D imaging technique. A camera records a time series of light scattering patterns as standard 2D images and then post-processing routines extract 3D information. By creating a GPU-accelerated GUI on top of the Holopy package, we noticed unexpected discrepancies between the different models used during post-processing.

Description

Digital holographic microscopy is a fast 3D imaging technique ideally suited to studies of micron-sized objects that diffuse through random walks via Brownian motion [1]. Microspheres fit this category and are widely used in biological assays and as ideal test subjects for experiments in statistical mechanics. Microspheres suspended in water move too quickly to monitor with confocal microscopy. With digital holographic microscopy, 2D images encoding 3D volumes can be recorded at thousands of frames per second [2]. The computationally challenging part of digital holographic microscopy is extracting the 3D information during post-processing.

The open source Holopy package which relies heavily on SciPy and NumPy is used to recover the 3D information via one of two techniques: reconstruction by numerical back-propagation of electromagnetic fields or modeling forward light scattering with Mie theory. The parameter space describing the imaged volume is multidimensional. Even for simple micron-sized spheres, a hologram depends on each sphere's radius and index of refraction in addition to its 3D position. By supplementing Holopy with a GPU-accelerated GUI using PyQt4, we enabled users to interactively adjust the system parameters and see a modeled digital hologram change in response.

Simply adding the capability of interactively manipulating holograms in a GUI led us to notice unexpected discrepancies between the two modeling techniques and failures of both, suggesting further experiments. We observed that the numerical light propagation technique only accurately characterizes the light within a cone stretching from the extent of the image back towards the object. Neither model accurately characterizes the light upstream of the object toward the light source. The GUI was a natural format to interact with the theory and gain insight because it showed us the models in an analogous format to how we see the data on the microscope. Other scientific projects may benefit from tools that allow experimentalists to interact with theory in the same way they interact with their experiments.

[1] Lee et.al., Optics Express, Vol. 15, Issue 26, pp. 18275-18282 (2007) doi: 10.1364/OE.15.018275.

[2] Kaz et.al., Nature Materials, Vol. 11, pp. 138013142 (2012) doi:10.1038/nmat3190.

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