The SVD Beamformer: Physical Principles and Application to Ultrafast Adaptive Ultrasound

Selective focusing through target identification and experimental acoustic signature extraction: Through-aberration experiments

In the first part of this work (Rodriguez et al. 2016), the selective focusing through identification and experimental acoustic signature extraction (SelF-EASE) method was presented, and its potential for accurate ultrasound focusing was assessed via numerical experiments. In the second part of this work, the inversion procedure and focusing signal extraction are improved in terms of reliability and computation time, and experimental results are presented. First, the improved signature extraction process is evaluated with two experimental aluminum samples. Second, the improved focusing process is experimentally performed on a target immersed in water behind an unknown aberration layer. Compared with the time-of-flight methods, the measured intensity fields greatly improve in terms of accuracy without any further knowledge of the medium.

Acoustic Cavitation Emissions Predict Near-complete/complete Histotripsy Treatment in Soft Tissues

OBJECTIVE

Histotripsy is a non-invasive acoustic ablation technique that leverages cavitation to impart mechanical damage to a viscoelastic medium, such as tissue. Although histotripsy bubbles and lesions can be imaged with a variety of modalities, reliable methods to predict tissue disruption across different tissue-types remain to be determined.

APPROACH

Several ex-vivo bovine tissues were ablated by intrinsic threshold histotripsy over a range of pulse-per-location acoustic doses. Acoustic Cavitation Emission (ACE) signals were captured following every other therapeutic pulse using transmit-receive capable histotripsy arrays. Final bubble lifespan, lifespan-slope, and percent-reduction were calculated and correlated against histologic necrosis score (0-5: 0=0% necrosis, 5=>95% necrosis) and residual structure score (0-4: 0=none present, 4=intact) to evaluate the ability of features from ACE-signals to predict histotripsy-induced damage. Further, optimal ACE-feature thresholds were determined for binary evaluation of whether a necrosis score equal or greater than 4 had been reached.

RESULTS

Measured lifespans increased and lifespan-slopes decreased with pulses per location (ppl) and eventually plateaued in all tissue types, in similar trends to those previously observed in tissue phantoms. Necrosis score increased and residual structure decreased with increasing acoustic dose. Bubble lifespan-slope and percent-reduction correlated well with necrosis score. Thresholds able to predict the necrosis score of 4 or greater in brain, liver, and kidney were calculated with high sensitivity/specificity (>80%). The necrosis score of 4 and 5 is expected to correspond to near-complete/complete ablation by histological evaluation.

CONCLUSION

Features measured from ACE-signals, particularly the lifespan-slope and percent reduction, were used to predict near-complete/complete ablation of large-volume histotripsy treatments in ex vivo bovine liver, kidney, and brain tissues with good accuracy. Tissue heterogeneities were observed to impact the histotripsy damage and corresponding ACE-signals, and thus the predication accuracy.

Mitigating Aberration-Induced Noise: A Deep Learning-Based Aberration-to- Aberration Approach

One of the primary sources of suboptimal image quality in ultrasound imaging is phase aberration. It is caused by spatial changes in sound speed over a heterogeneous medium, which disturbs the transmitted waves and prevents coherent summation of echo signals. Obtaining non-aberrated ground truths in real-world scenarios can be extremely challenging, if not impossible. This challenge hinders the performance of deep learning-based techniques due to the domain shift between simulated and experimental data. Here, for the first time, we propose a deep learning-based method that does not require ground truth to correct the phase aberration problem and, as such, can be directly trained on real data. We train a network wherein both the input and target output are randomly aberrated radio frequency (RF) data. Moreover, we demonstrate that a conventional loss function such as mean square error is inadequate for training such a network to achieve optimal performance. Instead, we propose an adaptive mixed loss function that employs both B-mode and RF data, resulting in more efficient convergence and enhanced performance. Finally, we publicly release our dataset, comprising over 180,000 aberrated single plane-wave images (RF data), wherein phase aberrations are modeled as near-field phase screens. Although not utilized in the proposed method, each aberrated image is paired with its corresponding aberration profile and the non-aberrated version, aiming to mitigate the data scarcity problem in developing deep learning-based techniques for phase aberration correction. Source code and trained model are also available along with the dataset at https://code.sonography.ai/main-aaa.

Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current state-of-the-art methods relate the tissue speed of sound to local echo shifts computed between images that are beamformed using restricted transmit and receive apertures. However, the aperture limitation affects the robustness of phase-shift estimations and, consequently, the accuracy of reconstructed speed-of-sound maps. Here, we propose a method based on the Radon transform of image patches able to estimate local phase shifts from full-aperture images. We validate our technique on simulated, phantom and in-vivo data acquired on a liver and compare it with a state-of-the-art method. We show that the proposed method enhances the stability to changes of beamforming speed of sound and to a reduction of the number of insonifications. In particular, the deployment of pulse-echo speed-of-sound estimation methods onto portable ultrasound devices can be eased by the reduction of the number of insonifications allowed by the proposed method.

Computational wave-based photoacoustic imaging through an unknown thick aberrating layer

We introduce a physics-based computational reconstruction framework for non-invasive photoacoustic tomography through a thick aberrating layer. Our wave-based approach leverages an analytic formulation of diffraction to beamform a photoacoustic image, when the aberrating layer profile is known. When the profile of the aberrating layer is unknown, the same analytical formulation serves as the basis for an automatic-differentiation regularized optimization algorithm that simultaneously reconstructs both the profile of the aberrating layer and the optically absorbing targets. Results from numerical studies and proof-of-concept experiments show promise for fast beamforming that takes into account diffraction effects occurring in the propagation through thick, highly-aberrating layers.

Phase Aberration Correction for In Vivo Ultrasound Localization Microscopy Using a Spatiotemporal Complex-Valued Neural Network

Ultrasound Localization Microscopy (ULM) can map microvessels at a resolution of a few micrometers ( [Formula: see text]). Transcranial ULM remains challenging in presence of aberrations caused by the skull, which lead to localization errors. Herein, we propose a deep learning approach based on recently introduced complex-valued convolutional neural networks (CV-CNNs) to retrieve the aberration function, which can then be used to form enhanced images using standard delay-and-sum beamforming. CV-CNNs were selected as they can apply time delays through multiplication with in-phase quadrature input data. Predicting the aberration function rather than corrected images also confers enhanced explainability to the network. In addition, 3D spatiotemporal convolutions were used for the network to leverage entire microbubble tracks. For training and validation, we used an anatomically and hemodynamically realistic mouse brain microvascular network model to simulate the flow of microbubbles in presence of aberration. The proposed CV-CNN performance was compared to the coherence-based method by using microbubble tracks. We then confirmed the capability of the proposed network to generalize to transcranial in vivo data in the mouse brain (n=3). Vascular reconstructions using a locally predicted aberration function included additional and sharper vessels. The CV-CNN was more robust than the coherence-based method and could perform aberration correction in a 6-month-old mouse. After correction, we measured a resolution of [Formula: see text] for younger mice, representing an improvement of 25.8%, while the resolution was improved by 13.9% for the 6-month-old mouse. This work leads to different applications for complex-valued convolutions in biomedical imaging and strategies to perform transcranial ULM.

Windowed Radon Transform and Tensor Rank-1 Decomposition for Adaptive Beamforming in Ultrafast Ultrasound

Ultrafast ultrasound has recently emerged as an alternative to traditional focused ultrasound. By virtue of the low number of insonifications it requires, ultrafast ultrasound enables the imaging of the human body at potentially very high frame rates. However, unaccounted for speed-of-sound variations in the insonified medium often result in phase aberrations in the reconstructed images. The diagnosis capability of ultrafast ultrasound is thus ultimately impeded. Therefore, there is a strong need for adaptive beamforming methods that are resilient to speed-of-sound aberrations. Several of such techniques have been proposed recently but they often lack parallelizability or the ability to directly correct both transmit and receive phase aberrations. In this article, we introduce an adaptive beamforming method designed to address these shortcomings. To do so, we compute the windowed Radon transform of several complex radio-frequency images reconstructed using delay-and-sum. Then, we apply to the obtained local sinograms weighted tensor rank-1 decompositions and their results are eventually used to reconstruct a corrected image. We demonstrate using simulated and in-vitro data that our method is able to successfully recover aberration-free images and that it outperforms both coherent compounding and the recently introduced SVD beamformer. Finally, we validate the proposed beamforming technique on in-vivo data, resulting in a significant improvement of image quality compared to the two reference methods.

Three-dimensional ultrasound matrix imaging

Matrix imaging paves the way towards a next revolution in wave physics. Based on the response matrix recorded between a set of sensors, it enables an optimized compensation of aberration phenomena and multiple scattering events that usually drastically hinder the focusing process in heterogeneous media. Although it gave rise to spectacular results in optical microscopy or seismic imaging, the success of matrix imaging has been so far relatively limited with ultrasonic waves because wave control is generally only performed with a linear array of transducers. In this paper, we extend ultrasound matrix imaging to a 3D geometry. Switching from a 1D to a 2D probe enables a much sharper estimation of the transmission matrix that links each transducer and each medium voxel. Here, we first present an experimental proof of concept on a tissue-mimicking phantom through ex-vivo tissues and then, show the potential of 3D matrix imaging for transcranial applications.

Aberration correction in diagnostic ultrasound: A review of the prior field and current directions

Medical ultrasound images are reconstructed with simplifying assumptions on wave propagation, with one of the most prominent assumptions being that the imaging medium is composed of a constant sound speed. When the assumption of a constant sound speed are violated, which is true in most in vivoor clinical imaging scenarios, distortion of the transmitted and received ultrasound wavefronts appear and degrade the image quality. This distortion is known as aberration, and the techniques used to correct for the distortion are known as aberration correction techniques. Several models have been proposed to understand and correct for aberration. In this review paper, aberration and aberration correction are explored from the early models and correction techniques, including the near-field phase screen model and its associated correction techniques such as nearest-neighbor cross-correlation, to more recent models and correction techniques that incorporate spatially varying aberration and diffractive effects, such as models and techniques that rely on the estimation of the sound speed distribution in the imaging medium. In addition to historical models, future directions of ultrasound aberration correction are proposed.

An aberration correction approach for single and dual aperture ultrasound imaging of the abdomen

Abdominal ultrasound image quality is hampered by phase aberration, that is mainly caused by the large speed-of-sound (SoS) differences between fat and muscle tissue in the abdominal wall. The mismatch between the assumed and actual SoS distribution introduces general blurring of the ultrasound images, and acoustic refraction can lead to geometric distortion of the imaged features. Large aperture imaging or dual-transducer imaging can improve abdominal imaging at deep locations by providing increased contrast and resolution. However, aberration effects for large aperture imaging can be even more severe, which limits its full potential. In this study, a model-based aberration correction method for arbitrary acquisition schemes is introduced for delay-and-sum (DAS) beamforming and its performance was analyzed for both single- and dual-transducer ultrasound imaging. The method employs aberration corrected wavefront arrival times, using manually assigned local SoS values. Two wavefront models were compared. The first model is based on a straight ray approximation, and the second model on the Eikonal equation, which is solved by a multi-stencils fast marching method. Their accuracy for abdominal imaging was evaluated in acoustic simulations and phantom experiments involving tissue-mimicking and porcine material with large SoS contrast (∼100 m/s). The lateral resolution was improved by up to 90% in simulations and up to 65% in experiments compared to standard DAS, in which the use of Eikonal beamforming generally outperformed straight ray beamforming. Moreover, geometric distortions were mitigated in multi-aperture imaging, leading to a reduction in position error of around 80%. A study on the sensitivity of the aberration correction to shape and SoS of aberrating layers was performed, showing that even with imperfect segmentations or SoS values, aberration correction still outperforms standard DAS.

Ultrasound Matrix Imaging-Part II: The Distortion Matrix for Aberration Correction Over Multiple Isoplanatic Patches

This is the second article in a series of two which report on a matrix approach for ultrasound imaging in heterogeneous media. This article describes the quantification and correction of aberration, i.e. the distortion of an image caused by spatial variations in the medium speed-of-sound. Adaptive focusing can compensate for aberration, but is only effective over a restricted area called the isoplanatic patch. Here, we use an experimentally-recorded matrix of reflected acoustic signals to synthesize a set of virtual transducers. We then examine wave propagation between these virtual transducers and an arbitrary correction plane. Such wave-fronts consist of two components: (i) An ideal geometric wave-front linked to diffraction and the input focusing point, and; (ii) Phase distortions induced by the speed-of-sound variations. These distortions are stored in a so-called distortion matrix, the singular value decomposition of which gives access to an optimized focusing law at any point. We show that, by decoupling the aberrations undergone by the outgoing and incoming waves and applying an iterative strategy, compensation for even high-order and spatially-distributed aberrations can be achieved. After a numerical validation of the process, ultrasound matrix imaging (UMI) is applied to the in-vivo imaging of a gallbladder. A map of isoplanatic modes is retrieved and is shown to be strongly correlated with the arrangement of tissues constituting the medium. The corresponding focusing laws yield an ultrasound image with drastically improved contrast and transverse resolution. UMI thus provides a flexible and powerful route towards computational ultrasound.

Ultrasound Matrix Imaging-Part I: The Focused Reflection Matrix, the F-Factor and the Role of Multiple Scattering

This is the first article in a series of two dealing with a matrix approach for aberration quantification and correction in ultrasound imaging. Advanced synthetic beamforming relies on a double focusing operation at transmission and reception on each point of the medium. Ultrasound matrix imaging (UMI) consists in decoupling the location of these transmitted and received focal spots. The response between those virtual transducers form the so-called focused reflection matrix that actually contains much more information than a confocal ultrasound image. In this paper, a time-frequency analysis of this matrix is performed, which highlights the single and multiple scattering contributions as well as the impact of aberrations in the monochromatic and broadband regimes. Interestingly, this analysis enables the measurement of the incoherent input-output point spread function at any pixel of this image. A fitting process enables the quantification of the single scattering, multiple scattering and noise components in the image. From the single scattering contribution, a focusing criterion is defined, and its evolution used to quantify the amount of aberration throughout the ultrasound image. In contrast to the state-of-the-art coherence factor, this new indicator is robust to multiple scattering and electronic noise, thereby providing a contrasted map of the focusing quality at a much better transverse resolution. After a validation of the proof-of-concept based on time-domain simulations, UMI is applied to the in-vivo study of a human calf. Beyond this specific example, UMI opens a new route for speed-of-sound and scattering quantification in ultrasound imaging.

Improving plane wave ultrasound imaging through real-time beamformation across multiple arrays

Ultrasound imaging is a widely used diagnostic tool but has limitations in the imaging of deep lesions or obese patients where the large depth to aperture size ratio (f-number) reduces image quality. Reducing the f-number can improve image quality, and in this work, we combined three commercial arrays to create a large imaging aperture of 100 mm and 384 elements. To maintain the frame rate given the large number of elements, plane wave imaging was implemented with all three arrays transmitting a coherent wavefront. On wire targets at a depth of 100 mm, the lateral resolution is significantly improved; the lateral resolution was 1.27 mm with one array (1/3 of the aperture) and 0.37 mm with the full aperture. After creating virtual receiving elements to fill the inter-array gaps, an autoregressive filter reduced the grating lobes originating from the inter-array gaps by - 5.2 dB. On a calibrated commercial phantom, the extended field-of-view and improved spatial resolution were verified. The large aperture facilitates aberration correction using a singular value decomposition-based beamformer. Finally, after approval of the Stanford Institutional Review Board, the three-array configuration was applied in imaging the liver of a volunteer, validating the potential for enhanced resolution.

Effects of phase aberration on transabdominal focusing for a large aperture, lowf-number histotripsy transducer

Objective. Soft tissue phase aberration may be particularly severe for histotripsy due to large aperture and lowf-number transducer geometries. This study investigated how phase aberration from human abdominal tissue affects focusing of a large, strongly curved histotripsy transducer.Approach.A computational model (k-Wave) was experimentally validated withex vivoporcine abdominal tissue and used to simulate focusing a histotripsy transducer (radius: 14.2 cm,f-number: 0.62, central frequencyfc: 750 kHz) through the human abdomen. Abdominal computed tomography images from 10 human subjects were segmented to create three-dimensional acoustic property maps. Simulations were performed focusing at 3 target locations in the liver of each subject with ideal phase correction, without phase correction, and after separately matching the sound speed of water and fat to non-fat soft tissue.Main results.Experimental validation in porcine abdominal tissue showed that simulated and measured arrival time differences agreed well (average error, ∼0.10 acoustic cycles atfc). In simulations with human tissue, aberration created arrival time differences of 0.65μs (∼0.5 cycles) at the target and shifted the focus from the target by 6.8 mm (6.4 mm pre-focally along depth direction), on average. Ideal phase correction increased maximum pressure amplitude by 95%, on average. Matching the sound speed of water and fat to non-fat soft tissue decreased the average pre-focal shift by 3.6 and 0.5 mm and increased pressure amplitude by 2% and 69%, respectively.Significance.Soft tissue phase aberration of large aperture, lowf-number histotripsy transducers is substantial despite low therapeutic frequencies. Phase correction could potentially recover substantial pressure amplitude for transabdominal histotripsy. Additionally, different heterogeneity sources distinctly affect focusing quality. The water path strongly affects the focal shift, while irregular tissue boundaries (e.g. fat) dominate pressure loss.

A theranostic 3D ultrasound imaging system for high resolution image-guided therapy

Microbubble contrast agents are a diagnostic tool with broad clinical impact and an increasing number of indications. Many therapeutic applications have also been identified. Yet, technologies for ultrasound guidance of microbubble-mediated therapy are limited. In particular, arrays that are capable of implementing and imaging microbubble-based therapy in three dimensions in real-time are lacking. We propose a system to perform and monitor microbubble-based therapy, capable of volumetric imaging over a large field-of-view. To propel the promise of the theranostic treatment strategies forward, we have designed and tested a unique array and system for 3D ultrasound guidance of microbubble-based therapeutic protocols based on the frequency, temporal and spatial requirements. Methods: Four 256-channel plane wave scanners (Verasonics, Inc, WA, USA) were combined to control a 1024-element planar array with 1.3 and 2.5 MHz therapeutic and imaging transmissions, respectively. A transducer aperture of ~40×15 mm was selected and Field II was applied to evaluate the point spread function. In vitro experiments were performed on commercial and custom phantoms to assess the spatial resolution, image contrast and microbubble-enhanced imaging capabilities. Results: We found that a 2D array configuration with 64 elements separated by λ-pitch in azimuth and 16 elements separated by 1.5λ-pitch in elevation ensured the required flexibility. This design, of 41.6 mm × 16 mm, thus provided both an extended field-of-view, up to 11 cm x 6 cm at 10 cm depth and steering of ±18° in azimuth and ±12° in elevation. At a depth of 16 cm, we achieved a volume imaging rate of 60 Hz, with a contrast ratio and resolution, respectively, of 19 dB, 0.8 mm at 3 cm and 20 dB and 2.1 mm at 12.5 cm. Conclusion: A single 2D array for both imaging and therapeutics, integrated with a 1024 channel scanner can guide microbubble-based therapy in volumetric regions of interest.

Spatiotemporal processing in photoplethysmography for skin microcirculatory perfusion imaging

Technological advances in the real-time visualization of cutaneous microcirculation aim to realize benefits including high-resolution imaging, suppressed noise, and robust temporal coherence. Photoplethysmography (PPG), a noninvasive technique that measures single or multiple points of relative blood volume changes in blood vessels under the skin, shows potential as a signal candidate for visualizing blood vessels and tracking blood flow. However, challenges still remain, such as extracting/image reconstruction of the blood vessel/flow signal in a precise frequency window (<0.2 Hz) from a noisy image that is caused by the loss of spatial coherence of the light source in a turbid biological tissue. We attempted to overcome this challenge by adopting a combination of direct-contact-type, lens-less, conformable imagers and singular value decomposition (SVD) in this study. We focused on the numerical analysis of SVD for discriminating the tissue and vein blood flow in PPG for reconstructing blood fluidic images, followed by a complete demonstration of skin microcirculation blood tracking in the vessel visualization process when applying our lens-less, conformable, wearable imagers.

The SVD beamformer with diverging waves: a proof-of-concept for fast aberration correction

The rise of ultrafast ultrasound imaging-with plane or diverging waves - paved the way to new applications of ultrasound in biomedical applications. However, propagation through complex layers (typically fat, muscle, and bone) hinder considerably the image quality, especially because of sound speed heterogeneities. In difficult-to-image patients, in the case of the hepatic steatosis for instance, a good image and a reliable sound speed quantification are crucial to provide a powerful non-invasive diagnosis tool. In this work, we proposed to adapt the singular value decomposition (SVD) beamformer method for diverging waves and thus present a novel aberration correction approach for widely used curved arrays. We probed its efficiency experimentally bothin vitroandin vivo. Besides the proposed matrix formalism, we explored the physical meaning of the SVD of ultrafast data. Finally, we demonstrated the ability of the technique to improve the image quality and offer new perspectives particularly in quantitative liver imaging.

Rotational-invariant speckle-scanning ultrasonography through thick bones

Ultrasonography is a major medical imaging technique that has been broadly applied in many disease diagnoses. However, due to strong aberration and scattering in the human skull, high-resolution transcranial ultrasonic imaging remains a grand challenge. Here, we explore the rotational-invariant property of ultrasonic speckle and develop high-resolution speckle-scanning ultrasonography to image sub-millimeter-sized features through thick bones. We experimentally validate the rotational invariance of ultrasonic speckle. Based on this property, we scan a random ultrasonic speckle pattern across an object sandwiched between two thick bones so that the object features can be encoded to the ultrasonic waves. After receiving the transmitted ultrasonic waves, we reconstruct the image of the object using an iterative phase retrieval algorithm. We successfully demonstrate imaging of hole and tube features sized as fine as several hundreds of microns between two 0.5 ~ 1-cm-thick bones. With 2.5-MHz excitation and the third-harmonic detection, we measure the spatial resolution as 352 µm. Rotational-invariant speckle-scanning ultrasonography offers a new approach to image through thick bones and paves an avenue towards high-resolution ultrasonic imaging of the human brain.

Retrobulbar blood flow in rat eyes during acute elevation of intraocular pressure

Most studies of the effect of acute elevation of intraocular pressure (IOP) on ocular blood-flow have utilized optical coherence tomography (OCT) to characterize retinal and choroidal flow and vascular density. This study investigates the effect of acute IOP elevation on blood flow velocity in the retrobulbar arteries and veins supplying and draining the eye, which, unlike the retinal and choroidal vasculature, are not directly compressed as IOP is increased. By cannulation of the anterior chamber of 20 Sprague-Dawley rats, we increased IOP in 10 mmHg steps from 10 to 60 mmHg and returned to 10 mmHg. After 1 min at each IOP (and 3 min after return to 10 mmHg), we acquired 18 MHz plane-wave ultrasound data at 3000 compound images/sec for 1.5 s. We produced color-flow Doppler images by digital signal processing of the ultrasound data, identified retrobulbar arteries and veins, generated spectrograms depicting flow velocity over the cardiac cycle and characterized changes of vascular density and perfusion in the orbit overall. Systolic, diastolic and mean velocities and resistive and pulsatile indices were determined from arterial spectrograms at each IOP level. Baseline mean arterial and mean venous velocities averaged 30.9 ± 10.8 and 8.5 ± 3.3 mm/s, respectively. Arterial velocity progressively decreased and resistance indices increased at and above an IOP of 30 mmHg. Mean arterial velocity at 60 mmHg dropped by 55% with respect to baseline, while venous velocity decreased by 20%. Arterial and venous velocities and resistance returned to near baseline after IOP was restored to 10 mmHg. Both vascular density and orbital perfusion decreased with IOP, but while perfusion returned to near normal when IOP returned to 10 mmHg, density remained reduced. Our findings are consistent with OCT-based studies showing reduced perfusion of the retina at levels comparable to retrobulbar arterial flow velocity change with increased IOP. The lesser effect on venous flow is possibly attributable to partial collapse of the venous lumen as volumetric venous outflow decreased at high IOP. The continued reduction in orbital vascular density 3 min after restoration of IOP to 10 mmHg might be attributable to persisting narrowing of capillaries, but this needs to be verified in future studies.

Advances in ultrasonography: image formation and quality assessment

Delay-and-sum (DAS) beamforming is widely used for generation of B-mode images from echo signals obtained with an array probe composed of transducer elements. However, the resolution and contrast achieved with DAS beamforming are determined by the physical specifications of the array, e.g., size and pitch of elements. To overcome this limitation, adaptive imaging methods have recently been explored extensively thanks to the dissemination of digital and programmable ultrasound systems. On the other hand, it is also important to evaluate the performance of such adaptive imaging methods quantitatively to validate whether the modification of the image characteristics resulting from the developed method is appropriate. Since many adaptive imaging methods have been developed and they often alter image characteristics, attempts have also been made to update the methods for quantitative assessment of image quality. This article provides a review of recent developments in adaptive imaging and image quality assessment.

Distortion matrix approach for ultrasound imaging of random scattering media

Focusing waves inside inhomogeneous media is a fundamental problem for imaging. Spatial variations of wave velocity can strongly distort propagating wave fronts and degrade image quality. Adaptive focusing can compensate for such aberration but is only effective over a restricted field of view. Here, we introduce a full-field approach to wave imaging based on the concept of the distortion matrix. This operator essentially connects any focal point inside the medium with the distortion that a wave front, emitted from that point, experiences due to heterogeneities. A time-reversal analysis of the distortion matrix enables the estimation of the transmission matrix that links each sensor and image voxel. Phase aberrations can then be unscrambled for any point, providing a full-field image of the medium with diffraction-limited resolution. Importantly, this process is particularly efficient in random scattering media, where traditional approaches such as adaptive focusing fail. Here, we first present an experimental proof of concept on a tissue-mimicking phantom and then, apply the method to in vivo imaging of human soft tissues. While introduced here in the context of acoustics, this approach can also be extended to optical microscopy, radar, or seismic imaging.