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Publication detail

Authors: B. Schneider, J. Dambre, P. Bienstman
Title: Fast particle characterization using digital holography and neural networks
Format: International Journal
Publication date: 1/2016
Journal/Conference/Book: Applied Optics
Editor/Publisher: OSA, 
Volume(Issue): 55(1) p.133-139
DOI: 10.1364/AO.55.000133
Citations: 12 (Dimensions.ai - last update: 18/4/2021)
6 (OpenCitations - last update: 19/4/2021)
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Abstract

We propose to use 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 mm and 20 mm we obtain accuracies of
(4.4 +- 0.2)% and (0.74 +- 0.01)% for the core and shell diameter, respectively.

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