Journal ArticleDOI
Autofocusing in digital holographic phase contrast microscopy on pure phase objects for live cell imaging
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TLDR
Results from investigations of an engineered surface and human pancreas tumor cells demonstrate the applicability of Fourier-weighting- and gradient-operator-based methods for robust and reliable automated subsequent numerical digital holographic focusing.Abstract:
Digital holography enables a multifocus quantitative phase microscopy for the investigation of reflective surfaces and for marker-free live cell imaging. For digital holographic long-term investigations of living cells an automated (subsequent) robust and reliable numerical focus adjustment is of particular importance. Four numerical methods for the determination of the optimal focus position in the numerical reconstruction and propagation of the complex object waves of pure phase objects are characterized, compared, and adapted to the requirements of digital holographic microscopy. Results from investigations of an engineered surface and human pancreas tumor cells demonstrate the applicability of Fourier-weighting- and gradient-operator-based methods for robust and reliable automated subsequent numerical digital holographic focusing.read more
Citations
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Journal ArticleDOI
Recent advances in holographic 3D particle tracking
Pasquale Memmolo,Lisa Miccio,Melania Paturzo,Giuseppe Di Caprio,Giuseppe Coppola,Paolo A. Netti,Pietro Ferraro +6 more
TL;DR: A complete review of state-of-the-art holographic 3D particle-tracking methods and their applications in bio-microfluidics is provided.
Book ChapterDOI
Quantitative Phase Imaging
Journal ArticleDOI
Simplified approach for quantitative digital holographic phase contrast imaging of living cells
TL;DR: Results from time-lapse investigations on living pancreas tumor cells demonstrate the capability of the Michelson interferometer approach for digital holographic microscopy for reliable quantitative phase contrast imaging.
Journal ArticleDOI
Extended depth-of-field in holographic image reconstruction using deep learning based auto-focusing and phase-recovery.
TL;DR: In this paper, a CNN is trained by using pairs of randomly de-focused back-propagated holograms and their corresponding in-focus phase-recovered images, and then the CNN takes a single backpropagation hologram of a 3D sample as input to rapidly achieve phase-recovery and reconstruct an in focus image of the sample over a significantly extended DOF.
Journal ArticleDOI
Early cell death detection with digital holographic microscopy.
Nicolas Pavillon,Jonas Kühn,Corinne Moratal,Pascal Jourdain,Christian Depeursinge,Pierre J. Magistretti,Pierre Marquet +6 more
TL;DR: The efficiency of this early regulation of cell volume detected by DHM, is correlated with the occurrence of subsequent neuronal death assessed with the widely accepted trypan blue method for detection of cell viability.
References
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Journal ArticleDOI
Simultaneous amplitude-contrast and quantitative phase-contrast microscopy by numerical reconstruction of Fresnel off-axis holograms
TL;DR: Off-axis holograms recorded with a magnified image of microscopic objects are numerically reconstructed in amplitude and phase by calculation of scalar diffraction in the Fresnel approximation to show that the transverse resolution is equal to the diffraction limit of the imaging system.
Journal ArticleDOI
Digital recording and numerical reconstruction of holograms
Ulf Schnars,Werner Jüptner +1 more
TL;DR: The principles and major applications of digital recording and numerical reconstruction of holograms (digital holography) are described, which are applied to measure shape and surface deformation of opaque bodies and refractive index fields within transparent media.
Journal ArticleDOI
Digital holographic microscopy: a noninvasive contrast imaging technique allowing quantitative visualization of living cells with subwavelength axial accuracy.
Pierre Marquet,Benjamin Rappaz,Pierre J. Magistretti,Etienne Cuche,Yves Emery,Tristan Colomb,Christian Depeursinge +6 more
TL;DR: A digital holographic microscope, in a transmission mode, especially dedicated to the quantitative visualization of phase objects such as living cells, is developed, based on an original numerical algorithm presented in detail elsewhere.
Journal ArticleDOI
A comparison of different focus functions for use in autofocus algorithms
TL;DR: Among the best focus functions found in this study are the squared magnitude gradient, the squared Laplacian, and the normalized image standard deviation.
Journal ArticleDOI
Autofocusing in computer microscopy: selecting the optimal focus algorithm.
TL;DR: This article presents a comprehensive comparison study of 18 focus algorithms in which a total of 139,000 microscope images were analyzed and guidelines allow for the selection of the optimal focus algorithm for different microscopy applications.
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