Nicolas Ducros

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Mid-infrared supercontinuum sources and application to FTIR spectromicroscopy

HAL (Le Centre pour la Communication Scientifique Directe) (2020)

Sébastien Février Laure Lavoute Kirill I. Zaytsev Dmitry Gaponov Ferenc Borondics

Supercontinuum

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Recurrent Neural Networks for Compressive Video Reconstruction

2022 IEEE 19th International Symposium on Biomedical Imaging (ISBI) (2020)

Antonio Lorente Mur Françoise Peyrin Nicolas Ducros

Single-pixel imaging allows low cost cameras to be built for imaging modalities where a conventional camera would either be too expensive or too cumbersome. This is very attractive for biomedical imaging applications based on hyperspectral measurements, such as image-guided surgery, which requires the full spectrum of fluorescence. A single-pixel camera essentially measures the inner product of the scene and a set of patterns. An inverse problem has to be solved to recover the original image from the raw measurement. The challenge in single-pixel imaging is to reconstruct the video sequence in real time from under-sampled data. Previous approaches have focused on the reconstruction of each frame independently, which fails to exploit the natural temporal redundancy in a video sequence. In this study, we propose a fast deep-learning reconstructor that exploits the spatio-temporal features in a video. In particular, we consider convolutional gated recurrent units that have low memory requirements. Our simulation shows than the proposed recurrent network improves the reconstruction quality compared to static approaches that reconstruct the video frames independently.

10.1109/isbi45749.2020.9098327

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Microscopie compressive hyperspectrale par feuillet de lumière structurée

HAL (Le Centre pour la Communication Scientifique Directe) (2022)

Sébastien Crombez Chloé Exbrayat-Héritier Florence Ruggiero Cédric Ray Nicolas Ducros

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Ultra broadband coupler . Based on dual-concentric-core photonic crystal fibre

HAL (Le Centre pour la Communication Scientifique Directe) (2008)

Frédéric Gérôme Nicolas Ducros F. Levesque Jean‐Louis Auguste Jean-Marc Blondy

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Time-resolved Diffuse Optical Tomography based on Single pixel camera

Biomedical optics (2016)

Andrea Farina Marta M. Betcke Nicolas Ducros Laura Di Sieno Andrea Bassi

In this work a time-resolved Diffuse Optical Tomography system based on rotating view acquisition and data sampling in compressed illumination/detection space is proposed and implemented. Reconstruction on tissue mimicking phantoms with absorbing inclusions are presented.

Diffuse optical imaging

Optical Tomography

10.1364/ots.2016.ow4d.3

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Acquisition adaptative pour single-pixel caméra : comparaison avec l’acquisition comprimée

HAL (Le Centre pour la Communication Scientifique Directe) (2016)

Florian Rousset Nicolas Ducros Andrea Farina Cosimo D’Andrea Françoise Peyrin

Les cameras mono-pixel (single-pixel camera, SPC) sont en plein essor ces dernieres annees car elles permettent d’obtenir un systeme d’imagerie optique a bas cout. Elles sont classiquement associees a des techniques d’acquisition comprimee (compressive sensing) pour l’acquisition et la reconstruction des images [1]. Nous proposons ici une nouvelle strategie qui produit des images de qualite comparable pour des temps de calcul et une complexite significativement reduits. Cette technique a potentiellement de multiples applications, par exemple en imagerie infrarouge ou multispectrale ou en imagerie de fluorescence resolue en temps.

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Prise en compte de contraintes expérimentales dans la conception de motifs pour caméra mono-pixel

HAL (Le Centre pour la Communication Scientifique Directe) (2017)

Florian Rousset Nicolas Ducros Françoise Peyrin

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Deep Hyperspectral microscopy based on structured light sheet

Imaging and Applied Optics Congress 2022 (3D, AOA, COSI, ISA, pcAOP) (2022)

Sébastien Crombez C Exbrayat-Heritier F Ruggerio C. Ray Nicolas Ducros

We describe a computational hyperspectral microscope based on a structured light sheet that is generated using a digital micromirror device only. To reduce the acquisition time, we consider a small number of structured patterns. We solve the resulting inverse problem using an unrolled deep neural network, which limits the loss of spatial resolution.

10.1364/cosi.2022.ctu5f.1

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Author Correction: All semiconductor enhanced high-harmonic generation from a single nanostructured cone

Scientific Reports (2020)

D. Franz Shatha Kaassamani David Gauthier Rana Nicolas Maria Kholodtsova

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Cone (formal languages)

Harmonic

10.1038/s41598-020-63113-5

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