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Convolutional neural networks for automated counting of single photon-upconversion nanoparticles in microfluidic chips
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SYSNO ASEP 0547470 Document Type A - Abstract R&D Document Type The record was not marked in the RIV R&D Document Type Není vybrán druh dokumentu Title Convolutional neural networks for automated counting of single photon-upconversion nanoparticles in microfluidic chips Author(s) Hlaváček, Antonín (UIACH-O) ORCID
Křivánková, Jana (UIACH-O) RID, ORCID
Foret, František (UIACH-O) RID, ORCIDNumber of authors 3 Source Title Book of abstracts of the 11th International Conference Analytical Cytometry, 1st edition. - Praha : AMCA, spol. s r.o., 2021 - ISBN 978-80-88214-26-7
S. 1-1Number of pages 1 s. Publication form Online - E Action International Conference Analytical Cytometry /11./ Event date 02.10.2021 - 05.10.2021 VEvent location Ostrava Country CZ - Czech Republic Event type WRD Language aba - abeština Country CZ - Czech Republic Keywords luminescence labels ; photon-upconversion nanoparticles ; single-molecule Subject RIV CB - Analytical Chemistry, Separation OECD category Analytical chemistry R&D Projects GA21-03156S GA ČR - Czech Science Foundation (CSF) Institutional support UIACH-O - RVO:68081715 Annotation Methods that allow the counting of single molecules advances current analytical chemistry. The reason is reaching the ultimate limit of detection, which a single molecule is. Previously, we have shown that photon-upconversion nanoparticles are excellent
luminescence labels for single-molecule immunochemical assays and applicable for droplet microfluidics.1-3 Here, we discuss current advancements of instrumentation, which are important for integrating single-molecule immunochemical assays of protein markers with microfluidics. The experimental device utilizes a laboratory-built epiluminescence microscope. High-intensity near-infrared excitation source enables imaging of single photon-upconversion labels, which are emitting visible wavelengths. The image data are recorded by an sCMOS camera up to 120 frames per second. Convolutional neural networks automatically process images and localize nanoparticles. The possibilities for multiplexing are discussed.Workplace Institute of Analytical Chemistry Contact Iveta Drobníková, drobnikova@iach.cz, Tel.: 532 290 234 Year of Publishing 2022
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