Plasmonic phase-imaging meta-sensors for cell classification

We investigate a convolutional neural network with the first layer implemented by specially designed plasmonic metasurface photodetectors, showing an order of magnitude decrease in computational complexity for the accurate classification of transparent biological cells.

Authors

Lei Tian (ORCID: https://orcid.org/0000-0002-1316-4456)
Janusz Konrad (ORCID: https://orcid.org/0000-0001-9283-5416)
Roberto Paiella (ORCID: https://orcid.org/0000-0002-7183-6249)
Jianing Liu (ORCID: https://orcid.org/0000-0002-3696-1829)
Haochuan Hu

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.1364/cleo_fs.2025.ff127_1
Primary Topic: Digital Holography and Microscopy
Type: article
Field-Weighted Citation Impact: 0.00

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article

Plasmonic phase-imaging meta-sensors for cell classification

Lei Tian, Janusz Konrad, Roberto Paiella, Jianing Liu et al.

Jan 1, 2025

Digital Holography and Microscopy

article

Plasmonic phase-imaging meta-sensors for cell classification

Lei Tian, Janusz Konrad, Roberto Paiella, Jianing Liu, Haochuan Hu

January 1, 2025article en

Abstract

We investigate a convolutional neural network with the first layer implemented by specially designed plasmonic metasurface photodetectors, showing an order of magnitude decrease in computational complexity for the accurate classification of transparent biological cells.

Openalex Percentile: Top 80%

Digital Holography and Microscopy

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Plasmonic phase-imaging meta-sensors for cell classification — Lei Tian, Janusz Konrad, et al. · (2025) | TGRS Research Map | TGRS