Holographic Tomography (HT) is an emerging label-free technique for microscopic bioimaging applications, that allows reconstructing the three-dimensional (3D) refractive index (RI) distribution of biological specimens. Recently, an inflow HT technique has been proposed in which multiple digital holograms are recorded at different viewing angles around the sample while it flows and rotates within a microfluidic channel. However, unlike conventional HT methods, there is no a priori information about cell 3D orientations, that are instead requested to perform any tomographic algorithm. Here we investigate a tracking-based rolling angles recovery method, showing robustness against the sample's features. It is based on a phase images similarity metric recently demonstrated, that exploits the local contrast phase measurements to recognize a full cell rotation within the microfluidic channel. Hence, the orientations of the flowing cells are retrieved from their positions, which are in turn computed through the 3D holographic tracking. The performances of the rolling angles recovery method have been assessed both numerically, by simulating a 3D cell phantom, and experimentally, by reconstructing the 3D RI tomograms of two cancer cells. Both the numerical and the experimental analysis have been performed at different spatial resolutions. This rolling angles recovery method, not depending on the cell shapes, the RI contents, and the optical experimental conditions, could pave the way to the study of circulating tumor cells (CTCs) in the challenging tool of liquid biopsy.

Tracking-based rolling angles recovery method for holographic tomography of flowing cells / Pirone, D.; Memmolo, P.; Merola, F.; Miccio, L.; Mugnano, M.; Capozzoli, A.; Curcio, C.; Liseno, A.; Ferraro, P.. - 11786:(2021). (Intervento presentato al convegno Optical Methods for Inspection, Characterization, and Imaging of Biomaterials V 2021 tenutosi a virtual nel 21 - 25 June 2021) [10.1117/12.2592591].

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

Pirone D.;Memmolo P.;Merola F.;Mugnano M.;Capozzoli A.;Curcio C.;Liseno A.;Ferraro P.
2021

Abstract

Holographic Tomography (HT) is an emerging label-free technique for microscopic bioimaging applications, that allows reconstructing the three-dimensional (3D) refractive index (RI) distribution of biological specimens. Recently, an inflow HT technique has been proposed in which multiple digital holograms are recorded at different viewing angles around the sample while it flows and rotates within a microfluidic channel. However, unlike conventional HT methods, there is no a priori information about cell 3D orientations, that are instead requested to perform any tomographic algorithm. Here we investigate a tracking-based rolling angles recovery method, showing robustness against the sample's features. It is based on a phase images similarity metric recently demonstrated, that exploits the local contrast phase measurements to recognize a full cell rotation within the microfluidic channel. Hence, the orientations of the flowing cells are retrieved from their positions, which are in turn computed through the 3D holographic tracking. The performances of the rolling angles recovery method have been assessed both numerically, by simulating a 3D cell phantom, and experimentally, by reconstructing the 3D RI tomograms of two cancer cells. Both the numerical and the experimental analysis have been performed at different spatial resolutions. This rolling angles recovery method, not depending on the cell shapes, the RI contents, and the optical experimental conditions, could pave the way to the study of circulating tumor cells (CTCs) in the challenging tool of liquid biopsy.
2021
9781510644069
9781510644076
Tracking-based rolling angles recovery method for holographic tomography of flowing cells / Pirone, D.; Memmolo, P.; Merola, F.; Miccio, L.; Mugnano, M.; Capozzoli, A.; Curcio, C.; Liseno, A.; Ferraro, P.. - 11786:(2021). (Intervento presentato al convegno Optical Methods for Inspection, Characterization, and Imaging of Biomaterials V 2021 tenutosi a virtual nel 21 - 25 June 2021) [10.1117/12.2592591].
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11588/866376
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact