| Authors: | A. Lugnan, J. Dambre, P. Bienstman | | Title: | Numerical investigation of integrated dielectric pillars to simplify machine learning classification of cells | | Format: | International Conference Proceedings | | Publication date: | 11/2018 | | Journal/Conference/Book: | 23rd Annual Symposium of the IEEE Photonics Benelux Chapter
| | Editor/Publisher: | IEEE Photonics Society - Benelux Chapter, | | Location: | Brussels, Belgium | | Citations: | Look up on Google Scholar
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Abstract
The computational power needed to classify interference patterns of biological cells is a major limit to the implementation of fast label-free cell sorting based on digital holographic microscopy and flow cytometry [1]. In this work we discuss some properties of a technique that employs a collection of integrated silica micro-pillars to significantly simplify the classification of raw holograms obtained from cells with different average nucleus size lighted by a laser. Related Research Topics
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