arXiv subjects

Guillaume Godefroy

Publications and source records attributed to Guillaume Godefroy.

4 recordsLinked to original sources

arXiv2024

Tailored 3D microphantoms: an essential tool for quantitative phase tomography analysis of organoids

We present a novel approach for benchmarking and validating quantitative phase tomography (QPT) systems using three-dimensional microphantoms. These microphantoms, crafted from biological and imaging data, replicate the optical and structural properties of multicellular biological samples. Their fabrication featuring refractive index modulation at sub-micrometer details is enabled by two-photon polymerization. We showcase the effectiveness of our technique via a round-robin test of healthy and tumoral liver organoid phantoms across three different QPT systems. This test reveals sample- and system-dependent errors in measuring dry mass and morphology. Tailored microphantoms establish the gold standard for the optimization of hardware setups, reconstruction strategies and error assessment, paving the way for novel non-invasive, label-free measurements of 3D biological samples.

physics.optics↗

arXiv2023

Speckle-correlation imaging through a kaleidoscopic multimode fiber

Speckle-correlation imaging techniques are widely used for non-invasive imaging through complex scattering media. While light propagation through multimode fibers and scattering media share many analogies, reconstructing images through multimode fibers from speckle correlations remains an unsolved challenge. Here, we exploit a kaleidoscopic memory effect emerging in square-core multimode fibers and demonstrate fluorescence imaging with no prior knowledge on the fiber. Experimentally, our approach simply requires to translate random speckle patterns at the input of a square-core fiber and to measure the resulting fluorescence intensity with a bucket detector. The image of the fluorescent object is then reconstructed from the autocorrelation of the measured signal by solving an inverse problem. This strategy does not require the knowledge of the fragile deterministic relation between input and output fields, which makes it promising for the development of flexible minimally-invasive endoscopes.

physics.optics↗

arXiv2020

Compensating for visibility artefacts in photoacoustic imaging with a deep learning approach providing prediction uncertainties

Conventional photoacoustic imaging may suffer from the limited view and bandwidth of ultrasound transducers. A deep learning approach is proposed to handle these problems and is demonstrated both in simulations and in experiments on a multi-scale model of leaf skeleton. We employed an experimental approach to build the training and the test sets using photographs of the samples as ground truth images. Reconstructions produced by the neural network show a greatly improved image quality as compared to conventional approaches. In addition, this work aimed at quantifying the reliability of the neural network predictions. To achieve this, the dropout Monte-Carlo procedure is applied to estimate a pixel-wise degree of confidence on each predicted picture. Last, we address the possibility to use transfer learning with simulated data in order to drastically limit the size of the experimental dataset.

eess.IV↗

arXiv2020

Photoacoustic fluctuation imaging: theory and application to blood flow imaging

Photoacoustic fluctuation imaging, which exploits randomness in photoacoustic generation, provides enhanced images in terms of resolution and visibility, as compared to conventional photoacoustic images. While a few experimental demonstrations of photoacoustic fluctuation imaging have been reported, it has to date not been described theoretically. In the first part of this work, we propose a theory relevant to fluctuations induced either by random illumination patterns or by random distributions of absorbing particles. The theoretical predictions are validated by Monte Carlo finite-difference time-domain simulations of photoacoustic generation in random particle media. We provide a physical insight into why visibility artefacts are absent from second-order fluctuation images. In the second part, we demonstrate experimentally that harnessing randomness induced by the flow of red blood cells produce photoacoustic fluctuation images free of visibility artefacts. As a first proof of concept, we obtain two-dimensional images of blood vessel phantoms. Photoacoustic fluctuation imaging is finally applied in vivo to obtain 3D images of the vascularization in a chicken embryo.

physics.optics↗