Aberration Correction Method Research Articles

A Deep Learning-Based Approach to Characterize Skull Physical Properties: A Phantom Study.

Transcranial ultrasound imaging is a popular method to study cerebral functionality and diagnose brain injuries. However, the detected ultrasound signal is greatly distorted due to the aberration caused by the skull bone. The aberration mechanism mainly depends on thickness and porosity, two important skull physical characteristics. Although skull bone thickness andporosity can be estimated from CT or MRI scans, there is significant value in developing methods for obtaining thickness and porosity information from ultrasound itself. Here, we extracted various features from ultrasound signals using physical skull-mimicking phantoms of a range of thicknesses with embedded porosity-mimicking acoustic mismatches and analyzed them using machine learning (ML) and deep learning (DL) models. The performance evaluation demonstrated that both ML- and DL-trained models could predict the physical characteristics of a variety of skull phantoms with reasonable accuracy. The proposed approach could be expanded upon and utilized for the development of effective skull aberration correction methods.

Improving SMF coupling efficiency in aberrated optical system through optical system aberration correction method based on MPLC

In spatial laser communication terminals, the distortion of wavefront caused by the aberrations due to optical system processing and installation errors reduces the coupling efficiency of single-mode fiber (SMF). A method based on Multi-Plane Light Conversion (MPLC) is proposed to correct optical system aberrations and improve the coupling efficiency by converting the distorted light into Gaussian beam which matches SMF through a succession of phase planes. The Gaussian beam to SMF coupling efficiency model is firstly established and demonstrates that the SMF coupling efficiency can be effectively improved to 100% by converting the incident light into Gaussian beam which matches the SMF mode. The optical system aberration correction comparison simulation and experiment is conducted, and the results show after correcting aberrations using MPLC, the coupling efficiency increases from less than 0.1%–58.61% compared to distorted light directly coupling into SMF. Results show that the optical system aberrations are effectively corrected by this method, which has a certain reference value for the study of improving the coupling efficiency.

Self-interference digital holography with computational aberration correction

Self-interference digital holography (SIDH) enables 3D imaging of incoherently emitting objects over a large axial range using only three 2D images. Our previous research demonstrated that point-like sources emitting as few as 4,200 photons can be reconstructed over a 10 µm axial range. Combining SIDH with single-molecule localization microscopy (SMLM) has the potential to achieve 3D super-resolution imaging across a large axial range without mechanical refocusing of the sample. However, optical aberrations affect the localization performance of SIDH and must be corrected, especially for large-volume 3D imaging. In this paper, we propose a fast, guide-star-free computational aberration correction method for SIDH. Our method can correct optical aberrations in low signal light conditions over the entire imaging axial range without any additional hardware. We use a sensorless-AO method in a virtual pupil plane to optimize the wavefront based on a frequency-space metric. Using this method, we demonstrate an improvement in both the Strehl ratio up to ∼0.98 and the SIDH localization precision to near the ideal case.

Transcranial ultrafast ultrasound Doppler imaging: A phantom study

Ultrafast ultrasound Doppler imaging facilitates the assessment of cerebral hemodynamics with high spatio-temporal resolution. However, the significant acoustic impedance mismatch between the skull and soft tissue results in phase aberrations, which can compromise the quality of transcranial imaging and introduce biases in velocity and direction quantification of blood flow. This paper proposed an aberration correction method that combines deep learning-based skull sound speed modelling with ray theory to realize transcranial plane-wave imaging and ultrafast Doppler imaging. The method was validated through phantom experiments using a linear array with a center frequency of 6.25 MHz, 128 elements, and a pitch of 0.3 mm. The results demonstrated an improvement in the imaging quality of intracranial targets when using the proposed method. After aberration correction, the average locating deviation decreased from 1.40 mm to 0.27 mm in the axial direction, from 0.50 mm to 0.20 mm in the lateral direction, and the average full-width-at-half-maximum (FWHM) decreased from 1.37 mm to 0.97 mm for point scatterers. For circular inclusions, the average contrast-to-noise ratio (CNR) improved from 8.1 dB to 11.0 dB, and the average eccentricity decreased from 0.36 to 0.26. Furthermore, the proposed method was applied to transcranial ultrafast Doppler flow imaging. The results showed a significant improvement in accuracy and quality for blood Doppler flow imaging. The results in the absence of the skull were considered as the reference, and the average normalized root-mean-square errors of the axial velocity component on the five selected axial profiles were reduced from 17.67% to 8.02% after the correction.

MINM: Marine intelligent netting monitoring using multi-scattering model and multi-space transformation

Marine intelligent net tank aquaculture monitoring plays an important role in improving aquaculture efficiency, environmental monitoring efficiency, and environmental safety. The underwater environment has complex light, often with problems such as scattering and absorption, resulting in poor image quality, making it difficult to accurately analyze and judge the aquaculture environment. Improving marine intelligent net tank aquaculture monitoring has the following three advantages: 1) better observation and monitoring of the aquaculture process, timely detection of problems and abnormalities, to protect the benefits of aquaculture and product quality. 2) more convenient and rapid monitoring of the aquaculture environment, improving monitoring efficiency and reducing monitoring costs. 3) effective monitoring of the underwater environment around the farm, and timely detection of foreign pollution, harmful substances, and other problems, to protect the safety of the aquaculture environment. Therefore, in order to solve the two degradation problems of scattering and absorption in the process of marine smart net farm monitoring, we propose a marine smart net farm monitoring method using multiple scattering models and multiple spatial transformations, called MINM. Specifically, inspired by the image chromatic aberration correction method, we design a color correction method in the multicolor space, which is implemented by using the Lab and RGB color space by performing contrast-constrained adaptive histogram equalization and gray world assumptions, respectively, to correct color shifts in different color models. Based on this, we propose a de-scattering method using a multi-scattering model, which eliminates the effect of scattering on underwater imaging by embedding a complete multi-scattering underwater imaging model to guide the extraction of different features in the multi-scattering model. To obtain more qualified results, we also propose an efficient perceptual fusion to mix the output of the de-scattering and color correction. Thus, our method can take advantage of multiple scattering models and multiple spatial transformations to effectively improve the visual quality of underwater images, producing enhanced results that fit the complete underwater imaging model and have bio-visual characteristics. In extensive experimental demonstrations, our MINM method has shown higher performance than the state-of-the-art methods in terms of both visual quality and quantitative metrics. All experimental results and datasets in this paper are available from the following website: https://github.com/An-Shunmin/MINM.

Research on aberration correction methods of conformal dome based on haack curve

Conformal optics arose from the need for better aerodynamic performance. The Haack curve has the lowest air drag under given conditions. It has superior aerodynamic properties compared to hemispherical domes and quadric conformal domes. Most in line with the concept of conformal optics. But aberration correction is also the most difficult. At present, there is no research on this conformal dome with the best aerodynamic performance. Therefore, a new design method for the internal surface is proposed in this paper to reduce the fluctuation range of aberrations. This method can eliminate the position error on the detector, reduce the fluctuation range of coma and spherical aberration, and even suppress the sensitivity of the defocus-field curvature to the parameters change. A condition for eliminating astigmatism is also proposed for the conformal dome. The fluctuation range of astigmatism and the difficulty of corrector design are reduced by reasonably choosing the rotation center. The research of this paper is of great significance in improving the aerodynamic performance of conformal optical systems.

Fourier space aberration correction for high resolution refractive index imaging using incoherent light

An aberration correction method is introduced for 3D phase deconvolution microscopy. Our technique capitalizes on multiple illumination patterns to iteratively extract Fourier space aberrations, utilizing the overlapping information inherent in these patterns. By refining the point spread function based on the retrieved aberration data, we significantly improve the precision of refractive index deconvolution. We validate the effectiveness of our method on both synthetic and biological three-dimensional samples, achieving notable enhancements in resolution and measurement accuracy. The method's reliability in aberration retrieval is further confirmed through controlled experiments with intentionally induced spherical aberrations, underscoring its potential for wide-ranging applications in microscopy and biomedicine.

Aberration correction by polynomial approximation for synthetic aperture ultrasound imaging

AbstractBackgroundPreviously, there has been some work in the field of optical imaging on phase compensation by employing Legendre polynomials as an expansion of the phase function, and this seems to be an appealing unstudied area in the field of ultrasound imaging.PurposeThe paper is devoted to solving one of the problems of enhancing the authenticity of diagnostics data obtained in ultrasound visualization systems and presents a novel approach to aberration correction, which ensures a reliable eliminating of phase distortions. The novelty of the proposed approach consists in the use of the decomposition of the wave front by Legendre polynomials to approximate aberrations of the phase front of ultrasonic waves propagating through distorting layers.MethodsThe phase aberrations are corrected using a single sector probe that captures echoes in synthetic aperture mode. The proposed method approximates the changes in the wave front by means of the Legendre polynomials. The performance was investigated by placing a 13‐mm‐wide ultrasonic probe with 64 elements operating at 2 MHz on the surface of a commercial quality control phantom ATS Model 539 through a distorting layer. The following metrics were measured: peak value, root mean square (RMS), full width at half maximum (FWHM), contrast‐to‐noise ratio (CNR). During the experiments, three different aberrators were used interchangeably as distorting layers, two of which were made of photopolymer resin with RMS values of 39 and 97 ns and a speed of sound close to that of a human temporal bone tissue, and the third was an ex vivo human temporal bone with the RMS value of 44 ns. To test the correction, three regions inside the phantom were examined. Two‐sided nonparametric Wilcoxon rank‐sum test was used for assessing the statistical significance. The significance level for this study was set at α ≤ 0.05. To counteract the problem of multiple comparisons, the p‐values were adjusted by the Holm–Bonferroni correction method.ResultsThe statistically significant results have demonstrated the possibility of increasing peak intensity value up to 3.08 times, reducing the RMS width and FWHM of the intensity angular distribution down to 60% and 82%, respectively, and increasing CNR up to 2.12 times by using the proposed phase distortion correction method, compared with the case without correction. The results show that the method can be used as an effective aberration correction technique for all tested regions inside the phantom and distorting layers. Its usage allowed correcting up to 97% of the aberrations caused by the ex vivo temporal bone model.ConclusionThe results show that the usage of the proposed method for aberration correction can successfully increase the intensity and reduce the angular width of the ultrasound wave scattered by the point targets inside the phantoms. The method works with different distorting layers and is capable of correcting phase aberrations in multiple sections of the sonogram. The limitation of the proposed method consists in the fact that it requires the use of aperture synthesis and access to raw radiofrequency data, which restricts its application in common scanners.

Treatment Planning and Aberration Correction Algorithm for HIFU Ablation of Renal Tumors.

High-intensity focused ultrasound (HIFU) applications for thermal or mechanical ablation of renal tumors often encounter challenges due to significant beam aberration and refraction caused by oblique beam incidence, inhomogeneous tissue layers, and presence of gas and bones within the beam. These losses can be significantly mitigated through sonication geometry planning, patient positioning, and aberration correction using multielement phased arrays. Here, a sonication planning algorithm is introduced, which uses the simulations to select the optimal transducer position and evaluate the effect of aberrations and acoustic field quality at the target region after aberration correction. Optimization of transducer positioning is implemented using a graphical user interface (GUI) to visualize a segmented 3-D computed tomography (CT)-based acoustic model of the body and to select sonication geometry through a combination of manual and automated approaches. An HIFU array (1.5 MHz, 256 elements) and three renal cell carcinoma (RCC) cases with different tumor locations and patient body habitus were considered. After array positioning, the correction of aberrations was performed using a combination of backpropagation from the focus with an ordinary least squares (OLS) optimization of phases at the array elements. The forward propagation was simulated using a combination of the Rayleigh integral and k-space pseudospectral method (k-Wave toolbox). After correction, simulated HIFU fields showed tight focusing and up to threefold higher maximum pressure within the target region. The addition of OLS optimization to the aberration correction method yielded up to 30% higher maximum pressure compared to the conventional backpropagation and up to 250% higher maximum pressure compared to the ray-tracing method, particularly in strongly distorted cases.

Machine Vision-Based Surface Defect Detection Study for Ceramic 3D Printing

A set of online inspection systems for surface defects based on machine vision was designed in response to the issue that extrusion molding ceramic 3D printing is prone to pits, bubbles, bulges, and other defects during the printing process that affect the mechanical properties of the printed products. The inspection system automatically identifies and locates defects in the printing process by inspecting the upper surface of the printing blank, and then feeds back to the control system to produce a layer of adjustment or stop the printing. Due to the conflict between the position of the camera and the extrusion head of the printer, the camera is placed at an angle, and the method of identifying the points and fitting the function to the data was used to correct the camera for aberrations. The region to be detected is extracted using the Otsu method (OSTU) on the acquired image, and the defects are detected using methods such as the Canny algorithm and Fast Fourier Transform, and the three defects are distinguished using the double threshold method. The experimental results show that the new aberration correction method can effectively minimize the effect of near-large selection caused by the tilted placement of the camera, and the accuracy of this system in detecting surface defects reached more than 97.2%, with a detection accuracy of 0.051 mm, which can meet the detection requirements. Using the weighting function to distinguish between its features and defects, and using the confusion matrix with the recall rate and precision as the evaluation indexes of this system, the results show that the detection system has accurate detection capability for the defects that occur during the printing process.

DeepFocus: fast focus and astigmatism correction for electron microscopy

High-throughput 2D and 3D scanning electron microscopy, which relies on automation and dependable control algorithms, requires high image quality with minimal human intervention. Classical focus and astigmatism correction algorithms attempt to explicitly model image formation and subsequently aberration correction. Such models often require parameter adjustments by experts when deployed to new microscopes, challenging samples, or imaging conditions to prevent unstable convergence, making them hard to use in practice or unreliable. Here, we introduce DeepFocus, a purely data-driven method for aberration correction in scanning electron microscopy. DeepFocus works under very low signal-to-noise ratio conditions, reduces processing times by more than an order of magnitude compared to the state-of-the-art method, rapidly converges within a large aberration range, and is easily recalibrated to different microscopes or challenging samples.

An <i>XY</i> defocus aberration correction method for high-energy lasers

An <i>XY</i> defocus aberration correction method for high-energy lasers

Low Spatio-temporal Frequency Wavefront Aberration Correction Method Based on a Movable Secondary Mirror

Low Spatio-temporal Frequency Wavefront Aberration Correction Method Based on a Movable Secondary Mirror

In Vivo Cavitation-Based Aberration Correction of Histotripsy in Porcine Liver.

Histotripsy is a noninvasive ablation technique that focuses ultrasound pulses into the body to destroy tissues via cavitation. Heterogeneous acoustic paths through tissue introduce phase errors that distort and weaken the focus, requiring additional power output from the histotripsy transducer to perform therapy. This effect, termed phase aberration, limits the safety and efficacy of histotripsy ablation. It has been shown in vitro that the phase errors from aberration can be corrected by receiving the acoustic signals emitted by cavitation. For transabdominal histotripsy in vivo, however, cavitation-based aberration correction (AC) is complicated by acoustic signal clutter and respiratory motion. This study develops a method that enables robust, effective cavitation-based AC in vivo and evaluates its efficacy in the swine liver. The method begins with a high-speed pulsing procedure to minimize the effects of respiratory motion. Then, an optimal phase correction is obtained in the presence of acoustic clutter by filtering with the singular value decomposition (SVD). This AC method reduced the power required to generate cavitation in the liver by 26% on average (range: 0%-52%) and required ~2 s for signal acquisition and processing per focus location. These results suggest that the cavitation-based method could enable fast and effective AC for transabdominal histotripsy.

An Automatic Calibration Method for the Field of View Aberration in a Risley-Prism-Based Image Sensor.

Risley-prism-based image sensors can expand the imaging field of view through beam control. The larger the top angle of the prism, the higher the magnification of the field of view, but at the same time, it aggravates the problem of imaging aberrations, which also puts higher requirements on the aberration correction method for the Risley-prism-based image sensor. To improve the speed, accuracy, and stability of the aberration correction process, an automatic calibration method for the Risley-prism-based image sensor is proposed based on a two-axis turntable. The image datasets of the calibration plate with different prism rotation angles and object distances are acquired using a two-axis turntable. Then, the images of the calibration plate are pre-processed using the bicubic interpolation algorithm. The calibration parameters are finally calculated, and parameter optimization is performed. The experimental results verify the feasibility of this automated calibration method. The reprojection error of the calibration is within 0.26 pixels when the distance of the imaging sensor is 3.6 m from the object, and the fine aberration correction results are observed.

Enhanced neuroimaging with a calcium sensor in ex-vivo Drosophila melanogaster brains using closed-loop adaptive optics light-sheet fluorescence microscopy.

Adaptive optics (AO) has been implemented on several microscopy setups and has proven its ability to increase both signal and resolution. However, reported configurations are not suited for fast imaging of live samples or are based on an invasive or complex implementation method. Provide a fast aberration correction method with an easy to implement AO module compatible with light-sheet fluorescence microscopy (LSFM) for enhanced imaging of live samples. Development of an AO add-on module for LSFM based on direct wavefront sensing without requiring a guide star using an extended-scene Shack-Hartmann wavefront sensor. The enhanced setup uses a two-color sample labeling strategy to optimize the photon budget. Fast AO correction of in-depth aberrations in an ex-vivo adult Drosophila brain enables doubling the contrast when imaging with either cell reporters or calcium sensors for functional imaging. We quantify the gain in terms of image quality on different functional domains of sleep neurons in the Drosophila brain at various depths and discuss the optimization of key parameters driving AO. We developed a compact AO module that can be integrated into most of the reported light-sheet microscopy setups, provides significant improvement of image quality and is compatible with fast imaging requirements such as calcium imaging.

Correcting spatial-spectral crosstalk and chromatic aberrations in broadband line-scan spectral-domain OCT images.

Digital correction of optical aberrations allows for high-resolution imaging across the full depth range in optical coherence tomography (OCT). Many digital aberration correction (DAC) methods have been proposed in the past to evaluate and correct monochromatic error in OCT images. However, other factors that deteriorate the image quality have not been fully investigated. Specifically, in a broadband line-scan spectral-domain OCT system (LS-SD-OCT), photons with different wavelengths scattered from the same transverse location and in the imaged object will be projected onto different spatial coordinates onto the 2D camera sensor, which in this work is defined as spatial-spectral crosstalk. In addition, chromatic aberrations in both axial and lateral directions are not negligible for broad spectral bandwidths. Here we present a novel approach to digital recovery of the spatial resolution in images acquired with a broadband LS-SD-OCT, which addresses these two main factors that limit the effectiveness of DAC for restoring diffraction-limited resolution in LS-SD-OCT images. In the proposed approach, spatial-spectral crosstalk and chromatic aberrations are suppressed by the registration of monochromatic sub-band tomograms that are digitally corrected for aberrations. The new method was validated by imaging a standard resolution target, a microspheres phantom, and different biological tissues. LS-SD-OCT technology combined with the proposed novel image reconstruction method could be a valuable research tool for various biomedical and clinical applications.

Neural invertible variable-degree optical aberrations correction.

Optical aberrations of optical systems cause significant degradation of imaging quality. Aberration correction by sophisticated lens designs and special glass materials generally incurs high cost of manufacturing and the increase in the weight of optical systems, thus recent work has shifted to aberration correction with deep learning-based post-processing. Though real-world optical aberrations vary in degree, existing methods cannot eliminate variable-degree aberrations well, especially for the severe degrees of degradation. Also, previous methods use a single feed-forward neural network and suffer from information loss in the output. To address the issues, we propose a novel aberration correction method with an invertible architecture by leveraging its information-lossless property. Within the architecture, we develop conditional invertible blocks to allow the processing of aberrations with variable degrees. Our method is evaluated on both a synthetic dataset from physics-based imaging simulation and a real captured dataset. Quantitative and qualitative experimental results demonstrate that our method outperforms compared methods in correcting variable-degree optical aberrations.

Phase aberration correction for ultrasound imaging guided extracorporeal shock wave therapy (ESWT): Feasibility study

Image guidance of extracorporeal shock wave therapy (ESWT) is important to enhance its efficacy while lowering pain in patients. Real-time ultrasound imaging is an appropriate modality for image guidance, but its image quality substantially reduces due to severe phase aberration from the different speed of sound between soft tissues and a gel pad, which is utilized to control a therapeutic focal point in ESWT. This paper presents a phase aberration correction method for improving image quality in the ultrasound imaging guided ESWT. To correct an error from phase aberration, a time delay based on a two-layer model with different speeds of sound is calculated for dynamic receive beamforming. For the phantom and in vivo studies, a rubber type gel pad (i.e., 1400 m/s) with a specific thickness (3 or 5-cm) was placed on the top of soft tissue and full scanline RF data were acquired. In the phantom study, with phase aberration correction, image quality was highly increased compared to image reconstructions with a fixed speed of sound (i.e., 1540 or 1400 m/s), i.e., 1.1 vs. 2.2 and 1.3 mm in −6dB lateral resolution and 0.64 vs. 0.61 and 0.56 in contrast-to-noise ratio (CNR), respectively. From an in vivo musculoskeletal (MSK) imaging, the phase aberration correction method provided a clearly improved depiction of muscle fibers in a rectus femoris region. These results indicate that the proposed method enables effective imaging guidance of ESWT by improving image quality of ultrasound imaging in real-time.

Adaptive correction method of hybrid aberrations in Fourier ptychographic microscopy.

Fourier ptychographic microscopy (FPM) enables quantitative phase imaging with a large field-of-view and high resolution by acquiring a series of low-resolution intensity images corresponding to different spatial frequencies stitched together in the Fourier domain. However, the presence of various aberrations in an imaging system can significantly degrade the quality of reconstruction results. The imaging performance and efficiency of the existing embedded optical pupil function recovery (EPRY-FPM) aberration correction algorithm are low due to the optimization strategy. An aberration correction method (AA-P algorithm) based on an improved phase recovery strategy is proposed to improve the reconstruction image quality. This algorithm uses adaptive modulation factors, which are added while updating iterations to optimize the spectral function and optical pupil function updates of the samples, respectively. The effectiveness of the proposed algorithm is verified through simulations and experiments using an open-source biological sample dataset. Experimental results show that the proposed AA-P algorithm in an optical system with hybrid aberrations, recovered complex amplitude images with clearer contours and higher phase contrast. The image reconstruction quality was improved by 82.6% when compared with the EPRY-FPM algorithm. The proposed AA-P algorithm can reconstruct better results with faster convergence, and the recovered optical pupil function can better characterize the aberration of the imaging system. Thus, our method is expected to reduce the strict requirements of wavefront aberration for the current FPM.