7 research outputs found

    Microscopie diffractive tomographique haute résolution : Numérisation d'échantillons optimisation et imagerie polarimétrique quantitative 3-D

    No full text
    Label-free imaging techniques are highly demanded for several applications in biology. Tomographic Diffractive Microscopy (TDM) is one of the well-established label-free Quantitative Phase Imaging technique. By using holographic system and numerical inversion models, TDM quantifies a weakly scattering sample’s 3-D refractive index (RI) distribution. Due to TDM’s sequential data acquisition, acquiring fewer holograms leads to faster imaging, but with a degraded image quality due to unrecorded object frequency components. Inspired by such problems, optimization of the angular sample scanning scheme is performed to obtain high quality images with limited number of holograms. Several classes of sample scanning schemes are studied. Image simulation considering transmission, reflection and 4Pi TDM configurations, as well as experimental validation using a transmission TDM reveals that the optimized scheme indeed better fills Fourier space, leading to better RI estimation. Moreover, TDM relying-on scalar-wave scattering theory leads to simplified data acquisitions and image reconstructions. It provides 3-D high-resolution RI maps of standard samples, however fails to quantify birefringent ones. In the second part of this work, a simplified polarization sensitive TDM (PS-TDM) system is built. The inversion algorithm is validated by image simulations using beam propagation method. Experiments are conducted using the optimized sample scanning scheme and variety of birefringent samples. Finally, use of a polarization analyzer sensor for PS-TDM allows mimicking a differential interference contrast microscopy, which is demonstrated experimentally using a non-birefringent sample.Les techniques d'imagerie sans marquage sont de plus en plus demandĂ©es. La microscopie tomographique diffractive (MTD) est une technique utilisant l’holographie et un modĂšle d'inversion numĂ©rique des donnĂ©es pour quantifier la distribution 3D de l'indice de rĂ©fraction (IR) de l’échantillon observĂ©. En raison de l'acquisition sĂ©quentielle des donnĂ©es en MTD, acquĂ©rir peu d’hologrammes permet une imagerie plus rapide, mais avec une qualitĂ© dĂ©gradĂ©e. Une optimisation du schĂ©ma d’illumination de l'Ă©chantillon a donc Ă©tĂ© effectuĂ©e pour obtenir des images de haute qualitĂ© avec un nombre limitĂ© d'hologrammes. Plusieurs types de schĂ©mas de balayage sont Ă©tudiĂ©s, par simulation en considĂ©rant les configurations en transmission, rĂ©flexion et 4Pi, et par validation expĂ©rimentale en utilisant un MTD en transmission. Le schĂ©ma de balayage optimisĂ© remplit mieux l'espace de Fourier, donnant une meilleure estimation de l'IR. La MTD basĂ©e sur la thĂ©orie scalaire de la diffraction permet une acquisition de donnĂ©es et une reconstruction d'image simplifiĂ©es. Elle fournit des cartes d'IR 3D Ă  haute rĂ©solution pour des spĂ©cimens standard, mais Ă©choue Ă  quantifier les Ă©chantillons birĂ©fringents. Dans la deuxiĂšme partie de ce travail, un systĂšme simplifiĂ© de MTD sensible Ă  la polarisation (MTD-SP) est construit. L'algorithme d'inversion est validĂ© par des simulations utilisant la mĂ©thode de propagation de faisceau. Des expĂ©riences sont menĂ©es en utilisant le schĂ©ma de balayage optimisĂ© et une variĂ©tĂ© d'Ă©chantillons birĂ©fringents. Enfin, l'utilisation d’un capteur de polarisation permet d'imiter un microscope Ă  contraste d'interfĂ©rence diffĂ©rentiel, ce qui a aussi Ă©tĂ© dĂ©montrĂ© expĂ©rimentalement

    Microscopie diffractive tomographique haute résolution : Numérisation d'échantillons optimisation et imagerie polarimétrique quantitative 3-D

    No full text
    Les techniques d'imagerie sans marquage sont de plus en plus demandĂ©es. La microscopie tomographique diffractive (MTD) est une technique utilisant l’holographie et un modĂšle d'inversion numĂ©rique des donnĂ©es pour quantifier la distribution 3D de l'indice de rĂ©fraction (IR) de l’échantillon observĂ©. En raison de l'acquisition sĂ©quentielle des donnĂ©es en MTD, acquĂ©rir peu d’hologrammes permet une imagerie plus rapide, mais avec une qualitĂ© dĂ©gradĂ©e. Une optimisation du schĂ©ma d’illumination de l'Ă©chantillon a donc Ă©tĂ© effectuĂ©e pour obtenir des images de haute qualitĂ© avec un nombre limitĂ© d'hologrammes. Plusieurs types de schĂ©mas de balayage sont Ă©tudiĂ©s, par simulation en considĂ©rant les configurations en transmission, rĂ©flexion et 4Pi, et par validation expĂ©rimentale en utilisant un MTD en transmission. Le schĂ©ma de balayage optimisĂ© remplit mieux l'espace de Fourier, donnant une meilleure estimation de l'IR. La MTD basĂ©e sur la thĂ©orie scalaire de la diffraction permet une acquisition de donnĂ©es et une reconstruction d'image simplifiĂ©es. Elle fournit des cartes d'IR 3D Ă  haute rĂ©solution pour des spĂ©cimens standard, mais Ă©choue Ă  quantifier les Ă©chantillons birĂ©fringents. Dans la deuxiĂšme partie de ce travail, un systĂšme simplifiĂ© de MTD sensible Ă  la polarisation (MTD-SP) est construit. L'algorithme d'inversion est validĂ© par des simulations utilisant la mĂ©thode de propagation de faisceau. Des expĂ©riences sont menĂ©es en utilisant le schĂ©ma de balayage optimisĂ© et une variĂ©tĂ© d'Ă©chantillons birĂ©fringents. Enfin, l'utilisation d’un capteur de polarisation permet d'imiter un microscope Ă  contraste d'interfĂ©rence diffĂ©rentiel, ce qui a aussi Ă©tĂ© dĂ©montrĂ© expĂ©rimentalement.Label-free imaging techniques are highly demanded for several applications in biology. Tomographic Diffractive Microscopy (TDM) is one of the well-established label-free Quantitative Phase Imaging technique. By using holographic system and numerical inversion models, TDM quantifies a weakly scattering sample’s 3-D refractive index (RI) distribution. Due to TDM’s sequential data acquisition, acquiring fewer holograms leads to faster imaging, but with a degraded image quality due to unrecorded object frequency components. Inspired by such problems, optimization of the angular sample scanning scheme is performed to obtain high quality images with limited number of holograms. Several classes of sample scanning schemes are studied. Image simulation considering transmission, reflection and 4Pi TDM configurations, as well as experimental validation using a transmission TDM reveals that the optimized scheme indeed better fills Fourier space, leading to better RI estimation. Moreover, TDM relying-on scalar-wave scattering theory leads to simplified data acquisitions and image reconstructions. It provides 3-D high-resolution RI maps of standard samples, however fails to quantify birefringent ones. In the second part of this work, a simplified polarization sensitive TDM (PS-TDM) system is built. The inversion algorithm is validated by image simulations using beam propagation method. Experiments are conducted using the optimized sample scanning scheme and variety of birefringent samples. Finally, use of a polarization analyzer sensor for PS-TDM allows mimicking a differential interference contrast microscopy, which is demonstrated experimentally using a non-birefringent sample

    Jones tomographic diffractive microscopy with a polarized array sensor

    No full text
    International audienceTomographic diffractive microscopy (TDM) based on scalar light-field approximation is widely implemented. Samples exhibiting anisotropic structures, however, necessitate accounting for the vectorial nature of light, leading to 3-D quantitative polarimetric imaging. In this work, we have developed a high-numerical aperture (at both illumination and detection) Jones TDM system, with detection multiplexing via a polarized array sensor (PAS), for imaging optically birefringent samples at high resolution. The method is first studied through image simulations. To validate our setup, an experiment using a sample containing both birefringent and non-birefringent objects is performed. Araneus diadematus spider silk fiber and Pinna nobilis oyster shell crystals are finally studied, allowing us to assess both birefringence and fast-axis orientation maps

    Unsupervised regularized inverse method for 3D reconstruction in tomographic diffractive microscopy

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    Regularized inverse approaches are now widely used for the three dimensional reconstructions in Tomographic Diffractive Microscopy. This family of methods consists in the minimization, under some constraints, of a cost function often composed with a data fidelity term and one or several regularization terms. On one hand, the data fidelity term is based on the likelihood of the data. On the other hand, the regularization terms are based on physical a priori (morphology, values,
). It is important to keep a good trade off between data fidelity and regularization. The contribution of these last ones is weighted through hyperparameters which require a precise tuning. The minimization of the Generalized Stein’s Unbiased Risk Estimator (GSURE) is efficient to select a set of optimal hyperparameters however it requires an accurate approximation of the data formation. In this work, we compare the efficiency of an unsupervised regularized approach using GSURE depending of the data model approximation. We compare the optimal reconstructions obtained using the first Born approximation on one side and the Beam Propagation Method on the other side. We chose the regularization of the Total Variation, which favor piece-wise constant structures. For the reconstruction, we used the Primal-Dual Condat-VĆ© algorithm with backtracking. We apply both reconstruction methods on experimental data. Our results show that our unsupervised regularized method manages in both cases to find an optimal reconstruction

    Reconstruction d’image rĂ©gularisĂ©e non supervisĂ©e en microscopie tomographique diffractive

    No full text
    Ce travail prĂ©sente une approche inverse rĂ©gularisĂ©e non supervisĂ©e pour la reconstruction de la carte 3D d’indice de rĂ©fraction d’un Ă©chantillon en microscopie tomographique diffractive (MTD), rĂ©cemment publiĂ©e dans le Journal of the Optical Society of America A (JOSAA) [1]. La technique MTD permet l’imagerie d’échantillons transparents en 3D sans requĂ©rir de marquage. La MTD apporte une information morphologique complĂ©mentaire aux phĂ©nomĂšnes mĂ©taboliques observĂ©s via les techniques de nanoscopie fluorescente (STED, PALM/STORM). Bien que moins rĂ©solue et moins spĂ©cifique que ces derniĂšres, la MTD permet tout de mĂȘme d’imager un champ de vue plus Ă©tendu Ă  haute rĂ©solution (2 fois la limite de diffraction). Notre mĂ©thode de reconstruction se base sur la minimisation de l’estimateur gĂ©nĂ©ralisĂ© non biaisĂ© du risque de Stein – GSURE pour Generalized Stein’s Unbiased Risk Estimator – afin d’estimer automatiquement des valeurs optimales des hyperparamĂštres de rĂ©gularisation (parcimonie, prĂ©servation de bords, Variation Totale). Nous avons Ă©valuĂ© cette mĂ©thode sur des reconstructions 3D Ă  partir de donnĂ©es simulĂ©es et expĂ©rimentales, en utilisant diffĂ©rents modĂšles de formation d’image (approximation de Rytov Ă  l’ordre 1, modĂšle de propagation de proche en proche – Beam Propagation Method), et en les comparant avec des mĂ©thodes de reconstruction usuelles (inversion de Rytov, algorithme de Gerchberg-Papoulis). Nos rĂ©sultats montrent qu’un rĂ©glage appropriĂ© du poids des rĂ©gularisations dans la rĂ©solution du problĂšme de reconstruction permet d’exploiter au mieux l’information disponible dans les donnĂ©es, ce qui peut s’avĂ©rer particuliĂšrement critique si cette derniĂšre est limitĂ©e (nombre d’angles de vues, couverture angulaire limitĂ©e). Disposer d’une mĂ©thode de rĂ©glage non supervisĂ©e de ces hyperparamĂštres constitue alors un avantage certain, et dans ce contexte nous montrons que le critĂšre GSURE est un bon candidat
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