Jaromír Běhal
38 Papers
2 Citations
Jaromír Běhal is an academic researcher. The author has contributed to research in topics: Computer science & Holography. The author has an hindex of 1, co-authored 2 publications.
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Papers
Intelligent polarization-sensitive holographic flow-cytometer: Towards specificity in classifying natural and microplastic fibers
Maria Rita Valentino,Jaromír Běhal,Vittorio Bianco,Simona Itri,Raffaella Mossotti,Giulia Dalla Fontana,Tiziano Battistini,Ettore Stella,Lisa Miccio,Pietro Ferraro +9 more
TL;DR: The proposed polarization-resolved holographic flow cytometer can accurately distinguish between different polymers under investigation, thus fulfilling the specificity goal, and extract and select different features from amplitude, phase and birefringence maps retrieved from the digital holograms.
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AI-aided holographic flow cytometry for label-free identification of ovarian cancer cells in the presence of unbalanced datasets
F. Borrelli,Jaromír Běhal,Adi Cohen,Lisa Miccio,Pasquale Memmolo,Ivana Kurelac,Amedeo Capozzoli,Claudio Curcio,Angelo Liseno,Vittorio Bianco,Natan T. Shaked,Pietro Ferraro +11 more
TL;DR: In this paper , the authors show that holographic flow cytometry is a valuable instrument to obtain quantitative phase-contrast maps as input data for artificial intelligence (AI)-based classifiers.
Developing a Reliable Holographic Flow Cyto-Tomography Apparatus by Optimizing the Experimental Layout and Computational Processing
Jaromír Běhal,F. Borrelli,Martina Mugnano,Vittorio Bianco,Amedeo Capozzoli,Claudio Curcio,Angelo Liseno,Lisa Miccio,Pasquale Memmolo,Pietro Ferraro +9 more
TL;DR: In this article , a quasi-common-path lateral-shearing holographic optical set-up was proposed for in-flow DHT in a flow-cytometer modality.
QPI assay of fibroblasts resilience to adverse effects of nanoGO clusters by multimodal and multiscale microscopy
Maria Rita Valentino,Daniel Pirone,Jaromír Běhal,Martina Mugnano,Rachele Castaldo,Giuseppe Cesare Lama,Pasquale Memmolo,Lisa Miccio,Vittorio Bianco,Simonetta Grilli,Pietro Ferraro +10 more
- 09 Jan 2024
TL;DR: It is shown how a multimodal QPI approach can furnish a non-invasive analysis for probing the dose-dependent effect of nanoGO clusters on adherent NIH 3T3 fibroblast cells.
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Label‐Free Imaging Flow Cytometry for Cell Classification Based on Multiple Interferometric Projections Using Deep Learning
Anat Cohen,Matan Dudaie,Itay Barnea,Francesca Borrelli,Jaromír Běhal,Lisa Miccio,Pasquale Memmolo,Vittorio Bianco,Pietro Ferraro,Natan T. Shaked +9 more
TL;DR: This approach is shown to be superior to that of using conventional 2D‐rotation augmentation, and can be used to decrease substantially the number of cell examples needed for training the classification model without impairing the results.
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