Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium

Liutkus, Antoine; Martina, David; Popoff, Sébastien M.; Chardon, Gilles; Katz, Ori; Lerosey, Geoffroy; Gigan, Sylvain; Daudet, Laurent; Carron, Igor

doi:10.1038/srep05552

Cited by 215 publications

(159 citation statements)

References 50 publications

Supporting

Mentioning

150

Contrasting

Unclassified

Order By: Relevance

“…One way to address such an issue resides in placing a scattering or heterogeneous medium in front of the US probe. This principle has been recently developed in optics and gives promising results [51]. However, such a new design raises many questions regarding the choice and the modelling of the heterogeneous medium.…”

Section: Psnr [Db]mentioning

confidence: 99%

Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction

Besson

Perdios

Martinez

et al. 2018

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

View full text Add to dashboard Cite

Abstract-Conventional ultrasound (US) image reconstruction methods rely on delay-and-sum (DAS) beamforming, which is a relatively poor solution of the image reconstruction problem. An alternative to DAS consists in using iterative techniques which require both an accurate measurement model and a strong prior on the image under scrutiny. Towards this goal, much effort has been deployed in formulating models for US imaging which usually require a large amount of memory to store the matrix coefficients. We present two different techniques which take advantage of fast and matrix-free formulations derived for the measurement model and its adjoint, and rely on sparsity of US images in well-chosen models. Sparse regularization is used for enhanced image reconstruction. Compressed beamforming exploits the compressed sensing framework to restore high quality images from fewer raw-data than state-of-the-art approaches. Using simulated data and in vivo experimental acquisitions, we show that the proposed approach is three orders of magnitude faster than non-DAS state-of-the-art methods, with comparable or better image quality.

show abstract

Section: Psnr [Db]mentioning

confidence: 99%

Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction

Besson

Perdios

Martinez

et al. 2018

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

View full text Add to dashboard Cite

show abstract

“…On a different scale, optical microscopy demands the ability to reach large depths, in particular when dealing with intra-vital microscopy 17 . Similarly, the physics of optics in random media 3,18,19 , and the attempts to improve focusing through scattering media need to model the depth profile of re-emitted photons [20][21][22][23] . The penetration depth of photons migrating in random media has been studied by several research groups [24][25][26][27][28][29][30][31][32][33][34][35][36][37] .…”

mentioning

confidence: 99%

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Vaessen

Saj̈

Lövblad

et al. 2016

Cortex

View full text Add to dashboard Cite

We propose a comprehensive statistical approach describing the penetration depth of light in random media. The presented theory exploits the concept of probability density function f(z|ρ, t) for the maximum depth reached by the photons that are eventually re-emitted from the surface of the medium at distance ρ and time t. Analytical formulas for f, for the mean maximum depth 〈z max 〉 and for the mean average depth z reached by the detected photons at the surface of a diffusive slab are derived within the framework of the diffusion approximation to the radiative transfer equation, both in the time domain and the continuous wave domain. Validation of the theory by means of comparisons with Monte Carlo simulations is also presented. The results are of interest for many research fields such as biomedical optics, advanced microscopy and disordered photonics.

show abstract

“…In this paper, we circumvent one major limitation of the previous proof-of-concept system [12]. Since optical sensors (here, a CCD camera) only measure the field intensity |y| 2 , in [12] the input image is phase-modulated using a phase-only SLM, with relative phases 0, π/4, π/2, and 3π/4.…”

Section: Introductionmentioning

confidence: 99%

Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach

Rajaei

Tramei

Gigan

et al. 2016

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Self Cite

View full text Add to dashboard Cite

In this paper, the problem of compressive imaging is addressed using natural randomization by means of a multiply scattering medium. To utilize the medium in this way, its corresponding transmission matrix must be estimated. For calibration purposes, we use a digital micromirror device (DMD) as a simple, cheap, and high-resolution binary intensity modulator. We propose a phase retrieval algorithm which is well adapted to intensity-only measurements on the camera, and to the input binary intensity patterns, both to estimate the complex transmission matrix as well as image reconstruction. We demonstrate promising experimental results for the proposed double phase retrieval algorithm using the MNIST dataset of handwritten digits as example images.

show abstract

Imaging With Nature: Compressive Imaging Using a Multiply Scattering Medium

Cited by 215 publications

References 50 publications

Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction

Ultrafast Ultrasound Imaging as an Inverse Problem: Matrix-Free Sparse Image Reconstruction

Structural white-matter connections mediating distinct behavioral components of spatial neglect in right brain-damaged patients

Intensity-only optical compressive imaging using a multiply scattering material and a double phase retrieval approach

Contact Info

Product

Resources

About