Sparsity-based reconstruction for super-resolved limited-view photoacoustic computed tomography deep in a scattering medium

Egolf, David; Chee, Ryan; Zemp, Roger J.

doi:10.1364/ol.43.002221

Cited by 23 publications

(22 citation statements)

References 14 publications

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“…Previous studies reported super-resolution images obtained via model-based reconstruction with sparsity priors on the imaged object, in the field of US imaging 30,31 and more recently in PA imaging 32 . In this work, we first illustrated the generality of the sparsity-constrained model-based approach by applying this method to obtain experimental PA and US images of sparse test objects, with the same imaging equipment being used in the PA and US experiments.…”

Section: Discussionmentioning

confidence: 99%

“…Second, the uncertainties of the forward model might have played a greater role in the US experiment. As a novelty of our work, we derived the forward model by measuring only one PSF, rather than all PSFs in the field of view, which was done, for instance, in 32 . This approach assumes that PSFs differ from each other only by time delays that are calculated based on wave propagation in water.…”

Section: Discussionmentioning

confidence: 99%

“…The matrix A A A can be modelled theoretically or measured experimentally. In some previous works, A A A was measured for each point of the reconstruction zone 14,15,32,34 . In our work, the matrix A A A is also obtained experimentally but we perform a measurement for only one point source.…”

Section: Forward Modelmentioning

confidence: 99%

“…The object to image was reconstructed over a cartesian grid with a L cc /10 = 12.5 µm step. As in previous works 30,32,34 , the value of the regularization parameter α was determined heuristically such that the reconstruction image was qualitatively close to the real sample. A 2D Gaussian filter and interpolation were applied to improve image visualization.…”

Section: Image Reconstructionmentioning

confidence: 99%

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Super-resolution photoacoustic and ultrasound imaging with sparse arrays

Vilov

Arnal

Hojman

et al. 2020

Sci Rep

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It has previously been demonstrated that model-based reconstruction methods relying on a priori knowledge of the imaging point spread function (PSF) coupled to sparsity priors on the object to image can provide super-resolution in photoacoustic (PA) or in ultrasound (US) imaging. Here, we experimentally show that such reconstruction also leads to super-resolution in both PA and US imaging with arrays having much less elements than used conventionally (sparse arrays). As a proof of concept, we obtained super-resolution PA and US cross-sectional images of microfluidic channels with only 8 elements of a 128-elements linear array using a reconstruction approach based on a linear propagation forward model and assuming sparsity of the imaged structure. Although the microchannels appear indistinguishable in the conventional delay-and-sum images obtained with all the 128 transducer elements, the applied sparsity-constrained model-based reconstruction provides super-resolution with down to only 8 elements. We also report simulation results showing that the minimal number of transducer elements required to obtain a correct reconstruction is fundamentally limited by the signal-to-noise ratio. The proposed method can be straigthforwardly applied to any transducer geometry, including 2D sparse arrays for 3D super-resolution PA and US imaging.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Forward Modelmentioning

confidence: 99%

Section: Image Reconstructionmentioning

confidence: 99%

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Super-resolution photoacoustic and ultrasound imaging with sparse arrays

Vilov

Arnal

Hojman

et al. 2020

Sci Rep

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“…2b for the L1 norm regularization has a significantly lower FWHM. This is attributed to the sparsity condition and must not necessarily be ascribed to the achievable resolution, although L1-based regularization has been shown to enhance the spatial resolution beyond the acoustic diffraction barrier [13]. Accurate reconstructions are similarly rendered when multiple microspheres are present in the ROI (Figs.…”

mentioning

confidence: 99%

Acoustic Scattering Mediated Single Detector Optoacoustic Tomography

et al. 2019

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Optoacoustic image formation is conventionally based upon ultrasound time-of-flight readings from multiple detection positions. Herein, we exploit acoustic scattering to physically encode the position of optical absorbers in the acquired signals, thus reduce the amount of data required to reconstruct an image from a single waveform. This concept is experimentally tested by including a random distribution of scatterers between the sample and an ultrasound detector array. Ultrasound transmission through a randomized scattering medium was calibrated by raster scanning a light-absorbing microparticle across a Cartesian grid. Image reconstruction from a single time-resolved signal was then enabled with a regularized model-based iterative algorithm relying on the calibration signals. The signal compression efficiency is facilitated by the relatively short acquisition time window needed to capture the entire scattered wavefield. The demonstrated feasibility to form an image using a single recorded optoacoustic waveform paves a way to the development of faster and affordable optoacoustic imaging systems.

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Broadband Model‐Based Optoacoustic Mesoscopy Enables Deep‐Tissue Imaging beyond the Acoustic Diffraction Limit

Hofmann

Rebling

et al. 2022

Laser & Photonics Reviews

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Optoacoustic mesoscopy (OAM) retrieves anatomical and functional contrast in vivo at depths not resolvable with optical microscopy. Recent progress on reconstruction algorithms have further advanced its imaging performance to provide high lateral resolution ultimately limited by acoustic diffraction. In this work, a new broadband model‐based OAM (MB‐OAM) framework efficiently exploiting scanning symmetries for an enhanced performance is presented. By capitalizing on the large detection bandwidth of a spherical polyvinylidene difluoride film while accurately accounting for its spatial impulse response, the new approach significantly outperforms standard OAM implementations in terms of contrast and resolution, as validated by functional in vivo experiments in mice and human volunteers. Furthermore, L1‐norm regularization enables resolving structures separated by less than the theoretical diffraction‐limited resolution. This unique label‐free angiographic performance demonstrates the general applicability of MB‐OAM as a super‐resolution deep‐tissue imaging method capable of breaking through the limits imposed by acoustic diffraction.

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Sparsity-based reconstruction for super-resolved limited-view photoacoustic computed tomography deep in a scattering medium

Cited by 23 publications

References 14 publications

Super-resolution photoacoustic and ultrasound imaging with sparse arrays

Super-resolution photoacoustic and ultrasound imaging with sparse arrays

Acoustic Scattering Mediated Single Detector Optoacoustic Tomography

Broadband Model‐Based Optoacoustic Mesoscopy Enables Deep‐Tissue Imaging beyond the Acoustic Diffraction Limit

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