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Herve Hugonnet

Bio: Herve Hugonnet is an academic researcher from KAIST. The author has contributed to research in topics: Physics & Medicine. The author has an hindex of 3, co-authored 14 publications receiving 24 citations.

Papers
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Journal ArticleDOI
06 May 2021
TL;DR: In this paper, the authors developed label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast, and demonstrated that different tumor types and a variety of precursor lesions and pathologies can be visualized with the present method.
Abstract: Histopathology relies upon the staining and sectioning of biological tissues, which can be laborious and may cause artifacts and distort tissues. We develop label-free volumetric imaging of thick-tissue slides, exploiting refractive index distributions as intrinsic imaging contrast. The present method systematically exploits label-free quantitative phase imaging techniques, volumetric reconstruction of intrinsic refractive index distributions in tissues, and numerical algorithms for the seamless stitching of multiple three-dimensional tomograms and for reducing scattering-induced image distortion. We demonstrated label-free volumetric imaging of thick tissues with the field of view of 2 mm × 1.75 mm × 0.2 mm with a spatial resolution of 170 nm × 170 nm × 1400 nm. The number of optical modes, calculated as the reconstructed volume divided by the size of the point spread function, was ∼20 giga voxels. We have also demonstrated that different tumor types and a variety of precursor lesions and pathologies can be visualized with the present method.

23 citations

Journal ArticleDOI
TL;DR: In this article, an optimization method based on simulated annealing is proposed to systematically obtain optimal illumination schemes that enable artifact-free deconvolution of unlabeled biological samples.
Abstract: In light transmission microscopy, axial scanning does not directly provide tomographic reconstruction of specimen. Phase deconvolution microscopy can convert a raw intensity image stack into a refractive index tomogram, the intrinsic sample contrast which can be exploited for quantitative morphological analysis. However, this technique is limited by reconstruction artifacts due to unoptimized optical conditions, which leads to a sparse and non-uniform optical transfer function. Here, we propose an optimization method based on simulated annealing to systematically obtain optimal illumination schemes that enable artifact-free deconvolution. The proposed method showed precise tomographic reconstruction of unlabeled biological samples.

17 citations

Posted Content
TL;DR: In this paper, an inverse problem solver that efficiently and directly computes inverse multiple scattering without making any assumptions is presented. But the inversion process is based on a physically intuitive approach and can be easily extended to other exact forward solvers.
Abstract: The inverse scattering problem, whose goal is to reconstruct an unknown scattering object from its scattered wave, is essential in fundamental wave physics and its wide applications in imaging sciences. However, it remains challenging to invert multiple scattering accurately and efficiently. Here, we exploit the modified Born series to demonstrate an inverse problem solver that efficiently and directly computes inverse multiple scattering without making any assumptions. The inversion process is based on a physically intuitive approach and can be easily extended to other exact forward solvers. We utilised the proposed method in optical diffraction tomography and numerically and experimentally demonstrated three-dimensional reconstruction of optically thick specimens with higher fidelity than those obtained using conventional methods based on the weak scattering approximation.

15 citations


Cited by
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Journal Article
TL;DR: In this article, a fast Fourier transform method of topography and interferometry is proposed to discriminate between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour generation techniques.
Abstract: A fast-Fourier-transform method of topography and interferometry is proposed. By computer processing of a noncontour type of fringe pattern, automatic discrimination is achieved between elevation and depression of the object or wave-front form, which has not been possible by the fringe-contour-generation techniques. The method has advantages over moire topography and conventional fringe-contour interferometry in both accuracy and sensitivity. Unlike fringe-scanning techniques, the method is easy to apply because it uses no moving components.

3,742 citations

01 Jan 2016
TL;DR: In this paper, the authors present the principles of optics electromagnetic theory of propagation interference and diffraction of light, which can be used to find a good book with a cup of coffee in the afternoon, instead of facing with some infectious bugs inside their computer.
Abstract: Thank you for reading principles of optics electromagnetic theory of propagation interference and diffraction of light. As you may know, people have search hundreds times for their favorite novels like this principles of optics electromagnetic theory of propagation interference and diffraction of light, but end up in harmful downloads. Rather than enjoying a good book with a cup of coffee in the afternoon, instead they are facing with some infectious bugs inside their computer.

2,213 citations

Journal ArticleDOI
TL;DR: This Roadmap article on digital holography provides an overview of a vast array of research activities in the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications.
Abstract: This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

36 citations

Journal ArticleDOI
12 Aug 2022-ACS Nano
TL;DR: In this article , the authors review recent advances in metasurface-based micro/nano-optical sensors and compare them with counterparts using micro-optics from aspects of physics, working principles, and applications.
Abstract: Metasurfaces are 2D artificial materials consisting of arrays of metamolecules, which are exquisitely designed to manipulate light in terms of amplitude, phase, and polarization state with spatial resolutions at the subwavelength scale. Traditional micro/nano-optical sensors (MNOSs) pursue high sensitivity through strongly localized optical fields based on diffractive and refractive optics, microcavities, and interferometers. Although detections of ultra-low concentrations of analytes have already been demonstrated, the label-free sensing and recognition of complex and unknown samples remain challenging, requiring multiple readouts from sensors, e.g., refractive index, absorption/emission spectrum, chirality, etc. Additionally, the reliability of detecting large, inhomogeneous biosamples may be compromised by the limited near-field sensing area from the localization of light. Here, we review recent advances in metasurface-based MNOSs and compare them with counterparts using micro-optics from aspects of physics, working principles, and applications. By virtue of underlying the physics and design flexibilities of metasurfaces, MNOSs have now been endowed with superb performances and advanced functionalities, leading toward highly integrated smart sensing platforms.

32 citations

Journal ArticleDOI
17 Dec 2020-eLife
TL;DR: The proposed method enables an automatic and quantitative spatiotemporal analysis of IS kinetics of morphological and biochemical parameters associated with IS dynamics, providing a new option for immunological research.
Abstract: The immunological synapse (IS) is a cell-cell junction between a T cell and a professional antigen-presenting cell. Since the IS formation is a critical step for the initiation of an antigen-specific immune response, various live-cell imaging techniques, most of which rely on fluorescence microscopy, have been used to study the dynamics of IS. However, the inherent limitations associated with the fluorescence-based imaging, such as photo-bleaching and photo-toxicity, prevent the long-term assessment of dynamic changes of IS with high frequency. Here, we propose and experimentally validate a label-free, volumetric, and automated assessment method for IS dynamics using a combinational approach of optical diffraction tomography and deep learning-based segmentation. The proposed method enables an automatic and quantitative spatiotemporal analysis of IS kinetics of morphological and biochemical parameters associated with IS dynamics, providing a new option for immunological research.

31 citations