Author

P. Ferraro

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioengineering· 2 Biophysics· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 2 Organism:human· 2 Research Focus:clustering· 1 Approach:deep learning· 1 Assay:flow cytometry· 1 Assay:imaging· 1 Approach:microscopy & imaging analysis· 1 Research Focus:spatial domain detection· 1

Frequent Co-Authors

D. Pirone· 3 shared L. Miccio· 3 shared M. Mugnano· 3 shared P. Memmolo· 3 shared F. Merola· 2 shared V. Bianco· 2 shared A. Capozzoli· 1 shared A. Iolascon· 1 shared

Activity by Year

2021-2021 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 39 mutual co-author links

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3 shared papersBioengineering

D. Pirone

Mutual co-authors in cluster

Author profile →

3 papers

Recent·Most cited

Stain-free nucleus identification in holographic learning flow cyto-tomography

D. Pirone, J. Lim, F. Merola, L. Miccio, M. Mugnano, V. Bianco, F. Cimmino, F. Visconte, A. Montella, M. Capasso, A. Iolascon, P. Memmolo, D. Psaltis, P. Ferraro

This paper introduces a computational method to identify cell nuclei in stain-free holographic flow cytometry data using statistical inference, validated against confocal microscopy.

bioRxiv · Dec 22, 2021 · PreprintBioengineering

Lipid droplets 3D full measurement by holographic in-flow tomography

D. Pirone, D. Sirico, L. Miccio, V. Bianco, M. Mugnano, D. Del Giudice, G. Pasquinelli, S. Valente, S. Lemma, L. Iommarini, I. Kurelac, P. Memmolo, P. Ferraro

This paper introduces a new method for 3D characterization of lipid droplets in cells using holographic in-flow tomography, enabling high-throughput analysis and improved spatial understanding.

bioRxiv · Dec 9, 2021 · PreprintBiophysics

Tracking-based rolling angles recovery method for holographic tomography of flowing cells

D. Pirone, P. Memmolo, F. Merola, L. Miccio, M. Mugnano, A. Capozzoli, C. Curcio, A. Liseno, P. Ferraro

This paper introduces a tracking-based method to recover rolling angles in holographic tomography of flowing cells, validated numerically and experimentally for cancer cells.

bioRxiv · Jun 1, 2021 · PreprintBioengineering