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Objectives CAD/CAM ceramic occlusal veneers are increasingly used as therapeutic options. However, little is known about their mechanical behavior under stress, as the response of the prepared tooth that supports it. The aim of this article is to use for the first time 3D color holography to evaluate the behavior of a molar occlusal veneer under stress and the response of the prepared tooth. Methods The occlusal surface of a lower molar is prepared to receive a specific monolithic ceramic reconstruction manufactured with a chairside CAD/CAM system. Longitudinally cut samples are used to get a planar object observation and to “look inside” the tooth. A digital holographic set-up permits to obtain the contact-less and one-shot measurement of the three-dimensional displacement field at the surface of the tooth sample; stain fields are evaluated with low noise-sensitive computation. Results Figures show the strain fields with micro-strain units and highlight the behavior of the ROI (region of interest) in the three directions of space. The ROI are: the ceramic, the glue junction, the dentin enamel junction, dentin and enamel. The results show an excellent behavior of the restored tooth without areas of excessive stress concentrations, but also a significant involvement of the dentin enamel junction. Significance The ceramic occlusal veneer seems to behave in accordance with the biomechanical concepts ensuring the longevity of the reconstituted tooth. 3D holography is a highly recommended method for studying dental biomechanics. [ABSTRACT FROM AUTHOR]

Abstract: This paper presents the experimental optical analysis of the crack inside an electronic component. The optical setup is used to carry out multidimensional deformation measurements using digital color holography and the spatial multiplexing of holograms. Since the Fresnel transform method depends on wavelength, a wavelength-dependent-zero-padding algorithm is described and results in a rigorous sizing of each reconstructed monochrome image. The criterion to optimize the parameters is presented and is based on minimizing the widening of the impulse response of the full recording/reconstruction process. The application of the proposed method is illustrated through the analysis of the mechanical deformation of the electronic component, and offers keys to understand its failure mode in industrial conditions. [Copyright &y& Elsevier]

This paper presents methods for vibration analysis using digital Fresnel holography. Methods are based on time averaging for forced oscillations and pulsed recording devoted to auto-oscillations. The two methods are applied to a clarinet reed. In the forced oscillation regime, the reed is excited by an acoustic wave with controlled frequency and amplitude such that the reconstructed holograms exhibit resolvable Bessel fringes. In the case of the auto-oscillation regime, the reed is placed in an artificial mouth. Deformation of the clarinet reed can be extracted with the recording of 3150 pulsed digital holograms. Experimental results show the vibration behaviour of the clarinet reed under forced and auto-oscillation regimes, exhibiting the modal structures and high amplitude shocks. [ABSTRACT FROM AUTHOR]

Digital holography is well adapted to measure any modifications related to any objects. The method refers to digital holographic interferometry where the phase change between two states of the object is of interest. However, the phase images are corrupted by the speckle decorrelation noise. In this paper, we address the question of de-noising in holographic interferometry when phase data are polluted with speckle noise. We present a new database of phase fringe images for the evaluation of de-noising algorithms in digital holography. In this database, the simulated phase maps present characteristics such as the size of the speckle grains and the noise level of the fringes, which can be controlled by the generation process. Deep neural network architectures are trained with sets of phase maps having differentiated parameters according to the features. The performances of the new models are evaluated with a set of test fringe patterns whose characteristics are representative of severe conditions in terms of input SNR and speckle grain size. For this, four metrics are considered, which are the PSNR, the phase error, the perceived quality index and the peak-to-valley ratio. Results demonstrate that the models trained with phase maps with a diversity of noise characteristics lead to improving their efficiency, their robustness and their generality on phase maps with severe noise.

Digital holography is a very efficient technique for 3D imaging and the characterization of changes at the surfaces of objects. However, during the process of holographic interferometry, the reconstructed phase images suffer from speckle noise. In this paper, de-noising is addressed with phase images corrupted with speckle noise. To do so, DnCNN residual networks with different depths were built and trained with various holographic noisy phase data. The possibility of using a network pre-trained on natural images with Gaussian noise is also investigated. All models are evaluated in terms of phase error with HOLODEEP benchmark data and with three unseen images corresponding to different experimental conditions. The best results are obtained using a network with only four convolutional blocks and trained with a wide range of noisy phase patterns.