Reflection Artifacts Research Articles

Dynamics of Dominance in Interacting Zebrafish

While two-body fighting behavior occurs throughout the animal kingdom to settle dominance disputes, important questions such as how the dynamics ultimately lead to a winner and loser are unresolved. Here we examine fighting behavior at high resolution in male zebrafish. We combine multiple cameras, a large volume containing a transparent interior cage to avoid reflection artifacts, with computer vision to track multiple body points across multiple organisms while maintaining individual identity in three dimensions. In the body point trajectories we find a spectrum of timescales which we use to build informative joint coordinates consisting of relative orientation and distance. We use the distribution of these coordinates to automatically identify fight epochs, and we demonstrate the postfight emergence of an abrupt asymmetry in relative orientations—a clear and quantitative signal of hierarchy formation. We identify short-time, multi-animal behaviors as clustered transitions between joint configurations, and show that fight epochs are spanned by a subset of these clusters, which we denote as maneuvers. The resulting space of maneuvers is rich but interpretable, including motifs such as “attacks” and “circling.” In the longer-time dynamics of maneuver frequencies we find differential and changing strategies, including that the eventual loser attacks more often towards the end of the contest. Our results suggest a reevaluation of relevant assessment models in zebrafish, while our approach is generally applicable to other animal systems. Published by the American Physical Society 2024

Reflection Artifacts Removal of Photoacoustic Imaging in Complex Medium

Abstract Photoacoustic (PA) imaging owns a great prospect in medical diagnosis because of its high contrast and capability in functional imaging. While, the detected PA signals are always a mix of direct-arrived signals (DAS) and reflected (scattered) signals (RS) in inhomogeneous and bounded samples such as human tissues. The RS can lead to many artifacts and severely affect the final image, which confuses the artifacts with the real PA sources. This paper employed a spatial singular value decomposition (SVD) filter to abstract the DAS and thus remove the reflection artifacts. We conducted experiments on an agar phantom and an in vitro tissue to verify the method. The results show that the proposed method can effectively remove RS, resulting in fewer reflection artifacts in PA images.

Illumination-adjustable photoacoustic and harmonic ultrasound for tracking magnetically driven microrobots.

The development of microrobots for biomedical applications has enabled tasks such as targeted drug delivery, minimally invasive surgeries, and precise diagnostics. However, effective in vivo navigation and control remain challenging due to their small size and complex body environment. Photoacoustic (PA) and ultrasound (US) imaging techniques, which offer high contrast, high resolution, and deep tissue penetration, are integrated to enhance microrobot visualization and tracking. Traditional imaging systems have a narrow effective illumination area, suffer from severe reflection artifacts, and are affected by strong electromagnetic fields. To address this, we present an illumination-adjustable PA and harmonic US imaging system with a customized pushrod mechanism for real-time focus adjustment. Experiments demonstrate high-resolution imaging and accurate microrobot positioning, showcasing the potential for biomedical applications, especially in minimally invasive procedures.

Extraction of laser stripe centerlines from translucent optical components using a multi-scale attention deep neural network

The precise extraction of laser stripe centerlines is critical for line-laser 3D scanning systems. However, conventional methods relying on threshold segmentation and morphological operations face significant challenges when confronted with pervasive optical phenomena, including specular reflection, scattering, and bleeding, which are commonly observed in translucent optical components. These methods typically require complex preprocessing procedures and often yield poor precision in centerline extraction. In this paper, we introduce a novel learning-based approach, complemented by a meticulously curated dataset, explicitly designed to address these challenges. Our proposed method leverages a multi-scale attention U-Net-like architecture, initially tasked with the segmentation of laser stripes from the complex background environment. Subsequently, it employs the Steger algorithm for the precise extraction of laser stripe centerlines. The experimental results, obtained by comprehensively evaluating real-world captured images, clearly demonstrate the effectiveness of our deep neural network combined with the Steger algorithm. This combined approach exhibits exceptional accuracy even when challenged by the interferences from specular reflection, scattering, and bleeding artifacts. Specifically, our method achieves a mean intersection over union (mIoU) of 84.71% for the laser stripe detection task, accompanied by a mean square error (MSE) of 10.371 pixels. Also, the average execution time for the centerline extraction task is notably efficient at 0.125 s.

Attention LSTM U-Net model for Drosophila melanogaster heart tube segmentation in optical coherence microscopy images.

Optical coherence microscopy (OCM) imaging of the Drosophila melanogaster (fruit fly) heart tube has enabled the non-invasive characterization of fly heart physiology in vivo. OCM generates large volumes of data, making it necessary to automate image analysis. Deep-learning-based neural network models have been developed to improve the efficiency of fly heart image segmentation. However, image artifacts caused by sample motion or reflections reduce the accuracy of the analysis. To improve the precision and efficiency of image data analysis, we developed an Attention LSTM U-Net model (FlyNet3.0), which incorporates an attention learning mechanism to track the beating fly heart in OCM images. The new model has improved the intersection over union (IOU) compared to FlyNet2.0 + with reflection artifacts from 86% to 89% and with movement from 81% to 89%. We also extended the capabilities of OCM analysis through the introduction of an automated, in vivo heart wall thickness measurement method, which has been validated on a Drosophila model of cardiac hypertrophy. This work will enable the comprehensive, non-invasive characterization of fly heart physiology in a high-throughput manner.

Building Teacher Personal Identity: An Autobiography of an Indonesian Non-native English Teacher

This research explores the professional identity formation of non-native English-speaking teachers (NNESTs) from a personal viewpoint, an area not extensively covered in existing literature. While there is a wealth of discussion on teacher professional identity, the subjective experiences of NNESTs in shaping their own identities are often overlooked. This autobiographical narrative study addresses this gap by examining my own experiences as an NNEST, integrating reflections from my time as a student and my practice as a teacher. Employing thematic analysis, this research scrutinizes reflection data and artifacts gathered throughout my academic and professional journey. This method allows for a comprehensive examination of how various experiences influence professional identity formation. The findings reveal that an NNEST's professional identity is significantly shaped by the professional context, which includes direct teaching experiences and teacher education, as well as the external political environment, such as government policies and efforts to improve educational quality. The study is particularly relevant in the context of developing countries, like Indonesia, highlighting the intricate relationship between personal experiences, professional settings, and the wider political context in the development of NNEST identities. This research contributes a unique perspective to the field of teacher identity and underscores the distinct challenges and influences that NNESTs encounter in their professional growth.

Preserving polarization maintaining photons for enhanced contrast imaging of the retina.

The purpose of this study is to demonstrate the feasibility of using polarization maintaining photons for enhanced contrast imaging of the retina. Orthogonal-polarization control has been frequently used in conventional fundus imaging systems to minimize reflection artifacts. However, the orthogonal-polarization configuration also rejects the directly reflected photons, which preserve the polarization condition of incident light, from the superficial layer of the fundus, i.e., the retina, and thus reduce the contrast of retinal imaging. We report here a portable fundus camera which can simultaneously perform orthogonal-polarization control to reject back-reflected light from the ophthalmic lens and parallel-polarization control to preserve the backscattered light from the retina which partially maintains the polarization state of the incoming light. This portable device utilizes miniaturized indirect ophthalmoscopy illumination to achieve non-mydriatic imaging, with a snapshot field of view of 101° eye-angle (67° visual-angle). Comparative analysis of retinal images acquired with a traditional orthogonal-polarization fundus camera from both normal and diseased eyes was conducted to validate the usefulness of the proposed design. The parallel-polarization control for enhanced contrast in high dynamic range imaging has also been validated.

Combined ARFI and Shear Wave Imaging of Prostate Cancer: Optimizing Beam Sequences and Parameter Reconstruction Approaches.

This study demonstrates the implementation of a shear wave reconstruction algorithm that enables concurrent acoustic radiation force impulse (ARFI) imaging and shear wave elasticity imaging (SWEI) of prostate cancer and zonal anatomy. The combined ARFI/SWEI sequence uses closely spaced push beams across the lateral field of view and simultaneously tracks both on-axis (within the region of excitation) and off-axis (laterally offset from the excitation) after each push beam. Using a large number of push beams across the lateral field of view enables the collection of higher signal-to-noise ratio (SNR) shear wave data to reconstruct the SWEI volume than is typically acquired. The shear wave arrival times were determined with cross-correlation of shear wave velocity signals in two dimensions after 3-D directional filtering to remove reflection artifacts. To combine data from serially interrogated lateral push locations, arrival times from different pushes were aligned by estimating the shear wave propagation time between push locations. Shear wave data acquired in an elasticity lesion phantom and reconstructed using this algorithm demonstrate benefits to contrast-to-noise ratio (CNR) with increased push beam density and 3-D directional filtering. Increasing the push beam spacing from 0.3 to 11.6 mm (typical for commercial SWEI systems) resulted in a 53% decrease in CNR. In human in vivo data, this imaging approach enabled high CNR (1.61-1.86) imaging of histologically-confirmed prostate cancer. The in vivo images had improved spatial resolution and CNR and fewer reflection artifacts as a result of the high push beam density, the high shear wave SNR, the use of multidimensional directional filtering, and the combination of shear wave data from different push beams.

3D least-squares reverse time migration in VTI media based on pseudoacoustic wave equation and multi-GPU parallel acceleration

As the high-density seismic acquisition is progressively becoming an essential mode of seismic exploration, developing high-precision imaging methods for 3D datasets has become an urgent industry requirement. Unfortunately, the two-dimensional least-squares reverse time migration (LSRTM) can hardly deal with the influence of the third dimension because the structure of reflectors is constantly changing in nearly all directions. Furthermore, anisotropy is very common in underground media, which makes the LSRTM based on isotropic assumption fail to locate the reflectors accurately and seriously limits the identification of geological stratification. Considering the above two problems, this paper derives the least-squares reverse time migration in three-dimensional vertical transversely isotropic media (3D-VTI-LSRTM) and develops a workflow which can realize 3D-LSRTM in VTI media based on this theory. Our workflow uses multi-GPU acceleration and heterogeneous CPU/GPU parallelism. Compared with the general parallel CPU workflow or single GPU workflow, it is feasible that the GPU application significantly improves computing efficiency in practical applications. In addition, this paper extends VTI-LSRTM from 2D to 3D, which solves the problem that the 2D algorithm cannot eliminate the lateral direction reflection artifacts. For the self-made 3D-VTI depression model and the 3D-VTI-SEG/EAGE salt model, we use four NVIDIA Tesla k40c graphics cards for testing. The results of the tests are correct and significantly improved compared to the 3D-VTI-RTM method.

Qualitative Comparison of Lock-in Thermography (LIT) and Pulse Phase Thermography (PPT) in Mid-Wave and Long-Wave Infrared for the Inspection of Paintings

When studying paintings with active infrared thermography (IRT), minimizing the temperature fluctuations and thermal shock during a measurement becomes important. Under these conditions, it might be beneficial to use lock-in thermography instead of the conventionally used pulse thermography (PT). This study compared the observations made with lock-in thermography (LIT) and pulse phase thermography (PPT) with halogen light excitation. Three distinctly different paintings were examined. The LIT measurements caused smaller temperature fluctuations and, overall, the phase images appeared to have a higher contrast and less noise. However, in the PPT phase images, the upper paint layer was less visible, an aspect which is of particular interest when trying to observe subsurface defects or the structure of the support. The influence of the spectral range of the cameras on the results was also investigated. All measurements were taken with a mid-wave infrared (MWIR) and long wave infrared (LWIR) camera. The results show that there is a significant number of direct reflection artifacts, caused by the use of the halogen light sources when using the MWIR camera. Adding a long-pass filter to the MWIR camera eliminated most of these artifacts. All results are presented in a side-by-side comparison.

On the Importance of Consistent Insonation Conditions During Hydrophone Calibration and Use.

Hydrophones are generally calibrated in acoustic fields with temporally localized (short pulse) or long duration (tone burst) signals. Free-field conditions are achieved by time gating any reflections from the hydrophone body, mounting structures, and surrounding water tank boundaries arriving at the active sensing element. Consequently, the sensitivity response of the hydrophone is a result of direct waves incident on its active element, free from any contaminating effects of reflections. However, when using tone bursts below 400 kHz to calibrate hydrophones, it may not be possible to isolate the direct wave from reflection artifacts. This means that the sensitivity responses derived at these frequencies using short pulse and tone burst signals might not be comparable as they can be characteristic of the acoustic field interaction with either/both the hydrophone active element alone or the hydrophone active element and body. Therefore, there is a need to consider an appropriate calibration method for a given hydrophone type, depending on whether the eventual application employs short pulse or tone burst acoustic fields. This article presents the findings from a short study comprising four needle-type hydrophones of active element diameters in the range of 1-4 mm. These hydrophones were calibrated from 30 kHz to 1.6 MHz using established calibration methodologies within the underwater acoustics (UWA) and ultrasound (US) areas employed at the National Physical Laboratory (NPL), Teddington, U.K. In UWA tone, burst acoustic fields are used, while in US, it is short pulses. The 2- and 4-mm-diameter needle hydrophones showed the largest variation at the overlapping frequencies, in which the maximum disagreement of UWA calibration was 30% relative to US calibration. For the 4-mm hydrophone, UWA calibration exhibited resonant sensitivity structure between 100 and 450 kHz, but which was absent in US calibration. This observed behavior was further investigated theoretically by using a validated acoustic wave solver to confirm the resonant sensitivity structure seen in the case of UWA calibration. The work contained within illustrates the need to ensure that the method of calibration is carefully considered in the context of the duration of the acoustic signals for which the hydrophone is intended.

Adaptive denoising of photoacoustic signal and image based on modified Kalman filter.

As a burgeoning medical imaging method based on hybrid fusion of light and ultrasound, photoacoustic imaging (PAI) has demonstrated high potential in various biomedical applications, especially in revealing the functional and molecular information to improve diagnostic accuracy. However, stemming from weak amplitude and unavoidable random noise, caused by limited laser power and severe attenuation in deep tissue imaging, PA signals are usually of low signal-to-noise ratio, and reconstructed PA images are of low quality. Despite that conventional Kalman filter (KF) can remove Gaussian noise in time domain, it lacks adaptability in real-time estimation due to its fixed model. Moreover, KF-based denoising algorithm has not been applied in PAI before. In this paper, we propose an adaptive modified KF (MKF) targeted at PAI denoising by tuning system noise matrix Q and measurement noise matrix R in the conventional KF model. Additionally, in order to compensate the signal skewing caused by MKF, we cascade the backward part of Rauch-Tung-Striebel smoother, which utilizes the newly determined Q. Finally, as a supplement, we add a commonly used differential filter to remove in-band reflection artifacts. Experimental results using phantom and ex vivo colorectal tissue are provided to prove validity of the algorithm.

Ultrasound image formation in the deep learning age

The success of diagnostic and interventional medical procedures is deeply rooted in the ability of modern imaging systems to deliver clear and interpretable information. After raw sensor data is received by ultrasound and photoacoustic imaging systems in particular, the beamforming process is often the first line of software defense against poor quality images. Yet, with today’s state-of-the-art beamformers, ultrasound and photoacoustic images remain challenged by channel noise, reflection artifacts, and acoustic clutter, which combine to complicate segmentation tasks and confuse overall image interpretation. These challenges exist because traditional beamforming and image formation steps are based on flawed assumptions in the presence of significant inter- and intrapatient variations.In this talk, I will introduce the PULSE Lab’s novel alternative to beamforming, which improves ultrasound and photoacoustic image quality by learning from the physics of sound wave propagation. We replace traditional beamforming steps with deep neural networks that only display segmented details, structures, and physical properties of interest. I will then transition to describing a new resource for the entire community to standardize and accelerate research at the intersection of ultrasound beamforming and deep learning. This resource includes the first internationally crowd-sourced database of raw ultrasound channel data and integrated beamforming and evaluation code (see https://cubdl.jhu.edu/ & https://pulselab.jhu.edu/ for more details).

Acoustic-resolution-based spectroscopic photoacoustic endoscopy towards molecular imaging in deep tissues.

Due to many technical difficulties, the study of molecular photoacoustic endoscopic (PAE) imaging in deep tissues is limited. In this work, we have set up a multimodal acoustic-resolution-based PAE (AR-PAE) system to image the rabbit rectum and preliminarily explored the potential of molecular PAE for deep-seated targets in proof-of-concept. We developed an improved back-projection (IBP) algorithm for focused detection over the centimeter-scale imaging depth. We also developed a deep-learning-based algorithm to remove the electrical noise from the step motor to prevent data averaging for reduced scanning time. We injected a dose of indocyanine green (ICG) near the rabbit rectum and compared 2D and 3D photoacoustic/ultrasound (PA/US) images at different wavelengths. We proposed incorporating a small camera to guide the slow PA/US endoscopic scan. Results show that this system has achieved a lateral resolution of about 0.77/0.65 mm for PA/US images with a signal-to-noise ratio (SNR) of 25/38 dB at an imaging depth of 1.4 cm. We found that the rectum wall and the ICG can be well distinguished spectroscopically. Results also show that the PA images at 532 nm have higher signal intensity and reflection artifacts from pelvic tendons and bones than those at longer wavelengths such as 800 nm. The proposed methods and the intuitive findings in this work may guide and promote the development of high-penetration molecular PAE.

Optimized Reconstruction Procedure of Photoacoustic Imaging for Reflection Artifacts Reduction.

Photoacoustic (PA) imaging technology is of some value in medical diagnoses such as breast cancer detection, vasculature imaging, and surgery navigating. While as most imaging objects are bounded, the received RF signals consist of the direct-arrived signals (DAS) from the PA sources and the boundary-reflected signals (BRS). The undesired BRS will severely impair the quality during the image reconstruction. They will bring in many artifacts and confuse the actual shape and location of the PA sources. We improved the reconstruction procedure by removing the BRS before the regular reconstruction process to suppress those artifacts. To verify our proposed method, we compared the results of the conventional and optimized procedures experimentally. In terms of qualitative observation, the reconstructed images by the optimized procedure illustrate fewer artifacts and more accurate shapes of the PA sources. To quantitatively evaluate the traditional and the optimized imaging procedure, we calculated the Distribution Relative Error (DRE) between each experiment result and its standard drawing of the phantoms. For both phantoms and the ex-vivo sample, the DREs of reconstruction result by the optimized reconstruction procedure decrease significantly. The results suggest that the optimized reconstruction process can effectively suppress the reflection artifacts and improve the shape accuracy of the PA sources.

21‐4: Implications of Spatial Coherence on Minimizing Diffractive Reflection Artifacts in OLED Displays

We demonstrate how spatial coherence affects the appearance of reflective artifacts in organic light‐emitting device (OLED) displays. We find that diffraction can account for a significant proportion of the diffuse reflection, and we provide a timely perspective on the degree to which these artifacts can be mitigated.

Limitations of Bedside Lung Ultrasound in Neonatal Lung Diseases.

Lung ultrasound is a technique that has rapidly developed in recent years. It is a low-cost, radiation-free, and easy-to-operate tool that can be repeatedly performed at the bedside. Compared to chest X-ray, lung ultrasound has high sensitivity and specificity in the diagnosis of neonatal respiratory distress syndrome, transient tachypnoea of newborns and pneumothorax. Lung ultrasound has been widely used in neonatal intensive care units. However, due to the physical barriers of air, where ultrasonic waves cannot pass and therefore reflection artifacts occur, it has limitations in some other lung diseases and cannot fully substitute for chest X-rays or CT/MRI scanning. This review describes these limitations in detail and highlights that if clinical symptoms are not effectively alleviated after medical treatment or the clinical presentation is not compatible with the ultrasound appearances, then chest X-rays or CT/MRI scanning should be performed to avoid misdiagnosis and mistreatment.

Weighted model-based optoacoustic reconstruction for partial-view geometries.

Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model-based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high-quality reconstructions for partial-view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model-based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial-view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial-view optoacoustic tomography data from a tissue-mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial-view-corrected weighted model-based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model-based and the weighted model-based algorithms. It is also demonstrated that the partial-view-corrected weighted model-based algorithm has the additional advantage of suppressing streaking artifacts due to the partial-view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial-view-corrected weighted model-based algorithm may prove useful for improving the quality of partial-view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.

Suppression of acoustic reflection artifact in endoscopic photoacoustic tomographic images based on approximation of ideal signals.

BACKGROUND: In endoscopic photoacoustic tomography (EPAT), the photoacoustically induced ultrasonic wave reflects at tissue boundaries due to the acoustic inhomogeneity of the imaged tissue, resulting in reflection artifacts (RAs) in the reconstructed images.OBJECTIVE: To suppress RAs in EPAT image reconstruction for improving the image quality.METHODS: A method was presented to render the cross-sectional images of the optical absorption with reduced RAs from acoustic measurements. The ideal photoacoustic signal was recovered from acoustic signals collected by the detector through solving a least square problem. Then, high-quality images of the optical absorption distribution were reconstructed from the ideal signal.RESULTS: The results demonstrated the improvement in the quality of the images rendered by this method in comparison with the conventional back-projection (BP) reconstructions. Compared with the short lag spatial coherence (SLSC) method, the peak signal-to-noise ratio (PSNR), normalized mean square absolute distance (NMSAD), and structural similarity (SSIM) were improved by up to 8%, 20%, and 5%, respectively.CONCLUSIONS: This method was capable of rendering images displaying the complex tissue types with reduced RAs and lower computational burden in comparison with previously developed methods.

Non-invasive and low-artifact in vivo brain imaging by using a scanning acoustic-photoacoustic dual mode microscopy

Photoacoustic imaging is a potential candidate for in vivo brain imaging, whereas, its imaging performance could be degraded by inhomogeneous multi-layered media, consisted of scalp and skull. In this work, we propose a low-artifact photoacoustic microscopy (LAPAM) scheme, which combines conventional acoustic-resolution photoacoustic microscopy with scanning acoustic microscopy to suppress the reflection artifacts induced by multi-layers. Based on similar propagation characteristics of photoacoustic signals and ultrasonic echoes, the ultrasonic echoes can be employed as the filters to suppress the reflection artifacts to obtain low-artifact photoacoustic images. Phantom experiment is used to validate the effectiveness of this method. Furthermore, LAPAM is applied for in-vivo imaging mouse brain without removing the scalp and the skull. Experimental results show that the proposed method successfully achieves the low-artifact brain image, which demonstrates the practical applicability of LAPAM. This work might improve the photoacoustic imaging quality in many biomedical applications which involve tissues with complex acoustic properties, such as brain imaging through scalp and skull.