Biology subjects

Pernot, M.

Publications and source records attributed to Pernot, M..

7 recordsLinked to original sources

bioRxiv2026

SVD-SN2N: Self-Inspired Noise2Noise Learning for Denoising Log-Compressed SVD-Filtered Ultrasound Imaging

Singular value decomposition (SVD) is the reference clutter rejection strategy for medical ultrafast ultrasound imaging, yet SVD filtered images retain a residual noise floor that obscures microvascular signals at depth. Supervised denoising cannot address this gap because clean references do not exist, and most physics-based alternatives require radio-frequency or in-phase/quadrature data that clinical scanners do not expose. We introduce SVD SN2N, a self supervised Noise2Noise framework that operates entirely on the post SVD image and requires neither clean targets nor channel level access. Our central contribution is to show that the residual fluctuations of SVD filtered images are dominated by multiplicative speckle, which violates the zero mean additive assumption of Noise2Noise theory, and that a single log compression step converts it into an additive perturbation whose variance no longer depends on the signal, restoring the conditions the framework requires. The log compressed image is split into two statistically independent half size copies by diagonal 2 times 2 resampling, rescaled by Fourier zero padding interpolation, and used to train a U Net under a self constrained twin-prediction loss. We assess the underlying assumptions directly by measuring the residual noise distribution, its spatial correlation and the signal similarity within diagonal pixel pairs, and we validate the framework on four heterogeneous datasets spanning preclinical and clinical, contrast enhanced and contrast-free, and 2D to 3D regimes. Relative to conventional SVD, SVD SN2N raises image derived SNR by 4.2 to10.6 dB and narrows the apparent vessel full width at half maximum by 34% to 59%, providing a post SVD denoising front end compatible with the image only data available on clinical scanners.

bioengineering↗

bioRxiv2026

Contrast-Free Microvascular and Functional Brain Imaging by Sparse Deconvolution of Ultrafast Power Doppler

Ultrafast power Doppler imaging combined with singular value decomposition (SVD) clutter filtering has become a standard approach for label-free microvascular ultrasound, enabling the visualization of small vessels without microbubble contrast agents. In the absence of contrast, however, SVD filtered Doppler images remain limited by the blur of the imaging system point spread function (PSF) and by a residual noise floor that reduces sensitivity at depth, which together hinder the resolution of fine microvasculature. Here we establish a sparse deconvolution framework to SVD filtered ultrafast power Doppler images. Each Doppler frame is processed in two cascaded stages: a Split-Bregman optimization that solves a regularized least-squares problem combining a sparsity prior and a Hessian continuity prior, followed by an accelerated Richardson Lucy deconvolution with an estimated system PSF. We first validated the framework on a simulation phantom with known ground truth, and then evaluated the framework on in vivo rat-brain plane-wave acquisitions obtained with a Verasonics Vantage system and a 15-MHz linear array. Compared to conventional SVD power Doppler, sparse deconvolution improved the resolution by around 4 and 8 times to lambda/2 and lambda/4, in the lateral and axial directions respectively. We further show that decomposing the Doppler signal into velocity bands before deconvolution disentangles slow and fast flow and yields a velocity-resolved microvascular map. Finally, applying the same framework to task-evoked functional ultrasound, we show that sparse deconvolution preserves the stimulus-locked cerebral-blood-volume response measured by conventional functional ultrasound while sharpening the corresponding activation map from a diffuse cortical region to discrete penetrating vessels. These results indicate that the sparsity-prior super-resolution principles established in label-free ultrafast Doppler ultrasound, and that sparse deconvolution can serve as a practical, contrast-free post-processing front-end for super-resolution microvascular and functional imaging.

bioengineering↗

bioRxiv2026

Multi-Stage Singular Value Decomposition for Ultrafast Ultrasound Imaging of Microbubbles

Microbubble contrast-enhanced ultrasound (CEUS) relies on discriminating nonlinear bubble signals from linear tissue backscattering. While Singular Value Decomposition (SVD) filtering improves this discrimination, existing techniques often fail to retain the slowly-moving microbubble signals from static clutter. Here, we present a novel multi-stage singular value decomposition (MS-SVD) framework for ultrafast CEUS imaging. Our method employs plane-wave transmissions at multiple angles and acoustic pressure levels (implemented via duty-cycle modulation) and alternating transmit polarity. The beamformed data are then processed by three sequential SVD filters: (1) spatial-angular SVD to extract coherent signals across all transmit angles, (2) spatial-pressure SVD to separate linear fundamental and nonlinear harmonic components, and (3) spatiotemporal SVD to isolate moving microbubble echoes from tissue clutter. In in vitro flow phantoms and in vivo rat brain through a cranial window, MS-SVD dramatically improves microbubble detection compared to conventional SVD filtering, MS-SVD yields much stronger vascular contrast and suppresses tissue clutter to a greater extent. The resulting power-Doppler and super-resolution maps are notably cleaner and more complete: MS-SVD detects substantially more microbubble events in ULM, revealing finer vessel details and more accurate flow speeds. By capturing the full acoustic signature of microbubbles (both fundamental and harmonic), MS-SVD achieves higher contrast-to-noise and sensitivity in CEUS. These gains make it a powerful front-end for super-resolution ultrasound localization microscopy and other high-sensitivity microvascular imaging applications.

bioengineering↗

bioRxiv2025

In vivo microvascular flow quantification in the mouse brain using Row-Column Ultrasound Localization Microscopy and directed graph analysis

Brain perfusion relies on a complex vascular network of arteries, veins, and capillaries to meet its constant demand for oxygen and nutrients. Disruption of this microvascular system is a hallmark of many neurological disorders, including small vessel disease, stroke, and brain tumors. As such, high-resolution in vivo imaging of cerebral microvascular flow and structure remains critical to understanding these pathologies. Among them, Ultrasound Localization Microscopy (ULM) allows noninvasive imaging of microvascular network at subwavelength resolution using injected microbubbles, but the approach remains mainly limited to 2D imaging with few volumetric implementations. In this study, we explore in vivo transcranial 3D ULM of the mouse brain using Row-Column Arrays (RCA) and introduce an analysis framework to build a flow-directed vascular graph from the ULM microbubble tracking data, allowing to differentiate between subgraphs of artery-like and vein-like vascular segments. Combined with Allen-based and Radius-based segmentations, we extract metrics including cerebral blood flow (CBF), microbubble (MB) velocity, flowrate, CBV fraction, vascular segment length and tortuosity in sixty-six different vascular classes. This high-sensitivity framework enables in vivo microvascular imaging and quantification in mice and provides a scalable platform for preclinical neurovascular studies in health and disease.

bioengineering↗

bioRxiv2025

Harmonic Amplitude-Modulated Singular Value Decomposition for Ultrafast Ultrasound Imaging of Gas Vesicles

Ultrafast nonlinear ultrasound imaging of gas vesicles (GV) contrast agents promises high-sensitivity biomolecular visualization with applications such as targeted molecular imaging of tumor markers or real-time tracking of gene expression. However, separating GV-specific signal from tissue remains challenging and requires the implementation of complex transmit schemes. In this work we introduce harmonic amplitude-modulated singular value decomposition (HAM-SVD), which synergizes pulse inversion (PI) with amplitude-modulated singular value decomposition (AM-SVD) to isolate GV-specific second-harmonic signals. In HAM-SVD, single-cycle plane waves at 9.6 MHz and five tilted angles (at a pulse repetition frequency of 2500 Hz) are transmitted under four duty cycles with alternating polarity. Beamformed IQ data are reshaped along a "space x pressure" matrix and decomposed via SVD; tissue background is cancelled by discarding the first and lowest singular modes, yielding an image comprised solely of pressure-dependent second harmonic signals. HAM-SVD sequence enables wide-field, ultrafast imaging without complex transmit sequences. Validation via simulations, in vitro phantoms, and in vivo rat lower limb experiments demonstrates HAM-SVDs outperformance compared to PI and AM-SVD. HAM-SVD is shown to achieve a 19.16 {+/-} 1.63 dB signal-to-background ratio (SBR) in vivo, surpassing PI (14.19 {+/-} 1.41 dB) and AM-SVD (15.79 {+/-} 1.38 dB). HAM-SVD overcomes limitations of conventional nonlinear techniques (e.g., depth restrictions, tissue clutter) by combining PIs harmonic sensitivity with AM-SVDs adaptive clutter filtering of tissue signals. This approach enhances molecular imaging specificity for GVs and holds potential for ultrasound localization microscopy of slow-flowing agents.

bioengineering↗

bioRxiv2021

Volumetric ultrasound localization microscopy of the whole brain microvasculature

Technologies to visualize whole organs across scales in vivo are essential for our understanding of biology in health and disease. To date, only post-mortem techniques such as perfused computed tomography scanning or optical microscopy of cleared tissues achieve cellular resolution across entire organs and imaging methods with equal performance in living mammalian organs have yet to be developed. Recently, 2D ultrasound localization microscopy has successfully mapped the fine-scale vasculature of various organs down to a 10 m precision. However, reprojection issues and out-of-plane motion prevent complex blood flow quantification and fast volumetric imaging of whole organs. Here, we demonstrate for the first time in vivo volumetric ultrasound localization microscopy mapping of the rodent brain vasculature. We developed a complete methodological pipeline that includes specific surgery, a dedicated 3D ultrasound acquisition sequence, localization and tracking algorithms, motion correction and realignment, as well as the post-processing quantification of cerebral blood flow. We illustrate the power of this approach, by mapping the whole rat brain vasculature at a resolution of 12 m, revealing mesoscopic to macroscopic vascular architectures and cerebral blood flows ranging from 1 to 100 mm/s. Our results pave the way to the investigation of in vivo vascular processes across the mammalian brain in health and disease, in a wide range of contexts and models.

bioengineering↗

bioRxiv2020

Repression of Pdzrn3 is required for heart maturation and protects against heart failure

Heart failure is the final common stage of most cardiopathies. Cardiomyocytes connect with others via their extremities by intercalated disk protein complexes. This planar and directional organization of myocytes is crucial for mechanical coupling and anisotropic conduction of the electric signal in the heart. One of the hallmarks of heart failure is alterations in the contact sites between cardiomyocytes. Yet no factor on its own is known to coordinate cardiomyocyte polarized organization. We report enhanced levels of an ubiquitine ligase Pdzrn3 in diseased hypertrophic human and mouse myocardium, which correlates with a loss of cardiomyocyte polarized elongation. We provide evidence that Pdzrn3 has a causative role in heart failure. We found that cardiac Pdzrn3 deficiency protected against heart failure while over expression of Pdzrn3 in mouse cardiomyocytes during the first weeks of life, impaired postnatal cardiomyocyte maturation leading to premature death. Our results reveal a novel signaling pathway that controls a genetic program essential for heart maturation and maintenance of overall geometry, as well as the contractile function of cardiomyocytes, and implicates PDZRN3 as a potential therapeutic target for the prevention of human heart failure.

physiology↗