Pasquale Memmolo,1 Daniele Pirone,1 Daniele G. Sirico,1 Lisa Miccio,1 Vittorio Bianco,1 Ahmed B. Ayoub,2 Demetri Psaltis,2 Pietro Ferrarohttps://orcid.org/0000-0002-0158-38561
1Istituto di Scienze Applicate e Sistemi Intelligenti "Eduardo Caianiello" (Italy) 2Ecole Polytechnique Fédérale de Lausanne (Switzerland)
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The recent development of tomographic phase imaging flow cytometry has unlocked the possibility to achieve data throughput comparable to the state-of-the-art imaging flow cytometry systems, but with the great advantages to be fully label-free and 3D. On the other hand, the huge amount of data to manage becomes one of the main computational problems to face with. Here we show that by using the 3D version of Zernike polynomials it is possible to efficiently encode single-cell phase-contrast tomograms, demonstrating high data compression capability with negligible information loss. A full simulative analysis is reported also quantifying the trade-off between compression factor and representation accuracy.
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Pasquale Memmolo, Daniele Pirone, Daniele G. Sirico, Lisa Miccio, Vittorio Bianco, Ahmed B. Ayoub, Demetri Psaltis, Pietro Ferraro, "Encoding single-cell phase-contrast tomograms by 3D Zernike descriptors," Proc. SPIE 12622, Optical Methods for Inspection, Characterization, and Imaging of Biomaterials VI, 126220C (11 August 2023); https://doi.org/10.1117/12.2674829