| 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: | 15 (Dimensions.ai - last update: 17/11/2024)
13 (OpenCitations - last update: 27/6/2024)
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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. Related Projects
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Citations (OpenCitations)
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