@inproceedings{7458ca1ed47c42d4ba7e5b6706751762,
title = "MULTIPHASE MICROFLOW MAPPING via DEFOCUSING micro-PTV",
abstract = "We use a defocusing-based micro-particle tracking velocimetry (µPTV) technique to map the 3D recirculation flow inside microfluidic droplets. We compare a deep learning model to cross-correlation to predict the Z-level, or depth, and report metrics of accuracy and precision. We implement regression models that output continuous Z-levels to improve the Z-resolution. These flow maps reveal fine topological detail of the droplets' recirculation flows and demonstrate the power of our method to precisely quantify 3D microflows.",
keywords = "deep learning, Droplet microfluidics, machine learning, particle tracking, PIV, PTV",
author = "Evan Lammertse and Nikhil Koditala and Martin Sauzade and Hongxiao Li and Jun Kong and Eric Brouzes",
note = "Publisher Copyright: {\textcopyright} 2021 MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences. All rights reserved.; 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2021 ; Conference date: 10-10-2021 Through 14-10-2021",
year = "2021",
language = "English",
series = "MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences",
publisher = "Chemical and Biological Microsystems Society",
pages = "1015--1016",
booktitle = "MicroTAS 2021 - 25th International Conference on Miniaturized Systems for Chemistry and Life Sciences",
}