High Signal-to-noise Ratio Imaging Research Articles

Multi-nanoparticle recognition and tracking based on SPTGAN-YOLOv3 modeling

Nanoparticle tracking techniques based on point spread function (PSF) engineering can monitor the movement of nanoparticles in 3D space in real time. However, increasing the axial tracking depth decreases the signal-to-noise ratio (SNR), which makes the reconstruction of nanoparticle trajectories more difficult. This paper proposes a deep learning-based object detection model SPTGAN-YOLOv3 for nanoparticle tracking technique. The SPTGAN-YOLOv3 model utilizes a noisy image with a low SNR as its input. It learns the mapping from noisy to noise-free images, generating a high SNR image. This rendered image is then used as the input for the object detection network, enabling the recognition and tracking of nanoparticles. Comparative analysis with conventional particle tracking methods demonstrates that the SPTGAN-YOLOv3 model significantly improves the precision and efficiency in recognizing and tracking multiple nanoparticles. Moreover, experimental results indicate that this technique notably enhances the SNR of nanoparticle tracking images and enables precise identification of nanoparticles.

Multiview Scattering Scanning Imaging Confocal Microscopy Through a Multimode Fiber

Confocal and multiphoton microscopy are effective techniques to obtain high-contrast images of 2-D sections within bulk tissue. However, scattering limits their application to depths only up to ∼1 millimeter. Multimode fibers make excellent ultrathin endoscopes that can penetrate deep inside the tissue with minimal damage. Here, we present Multiview Scattering Scanning Imaging Confocal (MUSSIC) Microscopy that enables high signal-to-noise ratio (SNR) imaging through a multimode fiber, hence combining the optical sectioning and resolution gain of confocal microscopy with the minimally invasive penetration capability of multimode fibers. The key advance presented here is the high SNR image reconstruction enabled by employing multiple coplanar virtual pinholes to capture multiple perspectives of the object, re-shifting them appropriately and combining them to obtain a high-contrast and high-resolution confocal image. We present the theory for the gain in contrast and resolution in MUSSIC microscopy and validate the concept through experimental results.

High signal-to-noise-ratio ultrasonic imaging of crack defects in particles filled composite explosives

<sec>Polymer bonded explosive (PBX) is a kind of composite material with highly filled molding explosive particles (normally more than 95%) and a small quantity of binders (less than 5%). The effective detection of internal cracks in PBX is of great significance in evaluating structural integrity and safety reliability.</sec><sec>Ultrasonic phased array detection and imaging methods show great advantages and potential in detecting crack defects. But acoustic test results indicate that the PBX has unique characteristics with low longitudinal wave velocity (～3000 m·s<sup>–1</sup>) and strong attenuation (attenuation coefficient ～400 dB·m<sup>–1</sup> for 2.5 MHz ultrasound). When the defect is imaged by traditional ultrasonic total focusing method (TFM), the structural noises at the boundaries between particles lead to low signal-to-noise ratio (SNR) in the FMC signals and strong background noise in reconstructed image, which will disturb the detection of cracks.</sec><sec>To realize the high SNR imaging of crack defects in PBX, an ultrasonic imaging algorithm based on baseband nonlinear synthetic focusing (BB-NSF) is proposed. By utilizing the spatial coherence of the received signals in full matrix capture (FMC) data, the pixel intensity at defect position can be enhanced while the background noise can be drastically weakened. The delay rule of the algorithm is modified according to the characteristics of PBX surface configuration. In this way, the high SNR imaging of crack defects with different orientations of PBX surface configuration is realized, and the quality of the reconstructed images is compared and evaluated quantitatively. Meanwhile, the base band transformation in calculation process optimization could significantly reduce calculation burden and increase imaging efficiency.</sec><sec>Experimental results show that the proposed algorithm can effectively suppress background noise and significantly improve the ability to detect the PBX cracks. The effective suppression to background noise makes the defect more highlighting and distinguished easily. For the BB-NSF algorithm, spatial coherence coefficient <i>p</i> is a crucial parameter used for dynamically regulating the SNR of reconstructed image. When <i>p</i> value is more than 2.0, the SNR of the ultrasonic reconstructed image of PBX crack defect is improved by more than 10 dB compared with that of the traditional linear synthetic focusing imaging. With the increase of <i>p</i> value, the SNR is further improved, while the calculation efficiency for a single image is almost kept stable. Moreover, the increase of SNR to some extent will improve the far-field detect capability.</sec><sec>Besides, with the BB-NSF algorithm, flexible transducer inhibits different imaging characteristics of for cracks with different orientations and depths in curved PBX specimens. For defects with large orientation angle and buried depth, the tip, root and shape of cracks can be completely present. For defects with small orientation angle and buried depth, part of shape and contour features will be lost.</sec><sec>In conclusion, the BB-NSF algorithm shows the advantage of high SNR and calculation efficiency in imaging PBX cracks, and exhibits great application prospect in imaging internal defects of other strongly attenuated composites.</sec>

Computational ghost imaging with PSF-guiding deep learning through various unknown turbid scattering media

Achieving high signal-to-noise ratio (SNR) imaging through scattering media is challenging. Computational ghost imaging with deep learning (CGIDL) has unique advantages for solving this challenge. However, image reconstruction cannot be guaranteed due to low correlation between real signal and training dataset, when the CGIDL is applied in different unknown scattering media. Point spread function (PSF) determines the quality of CGIDL reconstruction, linking the mathematical features of the scene and the quality of reconstruction. In this study, an innovative CGIDL technology based on the measured PSF method is proposed to improve the correlation between real signal and training dataset. When five new turbid scattering media with unknown scattering strength are introduced, classification of PSF enables high SNR imaging through various turbid scattering media.

Joint reconstruction and segmentation of noisy velocity images as an inverse Navier–Stokes problem

We formulate and solve a generalized inverse Navier–Stokes problem for the joint velocity field reconstruction and boundary segmentation of noisy flow velocity images. To regularize the problem, we use a Bayesian framework with Gaussian random fields. This allows us to estimate the uncertainties of the unknowns by approximating their posterior covariance with a quasi-Newton method. We first test the method for synthetic noisy images of two-dimensional (2-D) flows and observe that the method successfully reconstructs and segments the noisy synthetic images with a signal-to-noise ratio (SNR) of three. Then we conduct a magnetic resonance velocimetry (MRV) experiment to acquire images of an axisymmetric flow for low ( ${\simeq }6$ ) and high ( ${>}30$ ) SNRs. We show that the method is capable of reconstructing and segmenting the low SNR images, producing noiseless velocity fields and a smooth segmentation, with negligible errors compared with the high SNR images. This amounts to a reduction of the total scanning time by a factor of 27. At the same time, the method provides additional knowledge about the physics of the flow (e.g. pressure) and addresses the shortcomings of MRV (i.e. low spatial resolution and partial volume effects) that otherwise hinder the accurate estimation of wall shear stresses. Although the implementation of the method is restricted to 2-D steady planar and axisymmetric flows, the formulation applies immediately to three-dimensional (3-D) steady flows and naturally extends to 3-D periodic and unsteady flows.

Intelligent denoise laser ultrasonic imaging for inspection of selective laser melting components with rough surface

The random microdefects are inevitable during the Selective laser melting (SLM) process due to the principle of discrete-stacking. The rough surface induced strong background noise reduces the probability of detection of traditional laser ultrasonic testing system. In this study, an intelligent denoise laser ultrasonic imaging method was developed to inspect the micro defects on the rough surface of SLM components: (1) a non-contact laser ultrasonic scanning setup was established for data acquisition of multiple ultrasonic signals; (2) a denoising algorithm based on unsupervised machine learning was designed and trained by abundant ultrasonic data to enhance the signal to noise ratio (SNR); (3) a signal matching algorithm based on the cross-correlation and self-normalized method was established to match the amplitude and arrival time of Rayleigh waves from different scanning points. The performance of developed method was verified using micro hole defects on the rough surface of a SLM part. The results indicated that the established denoising algorithm could increase the average SNR from 27.0 dB to 35.2 dB. All holes with diameter of 50 μm and 100 μm can be detected and sized based on the high SNR image without removing the rough surface. The conclusion can be drawn that the proposed intelligent denoise laser ultrasonic imaging method is a very potential way for the online inspection of SLM.

Reconfigurable time-frequency division multiplexing metasurface: giving a helping hand to high signal-to-noise ratio and high data holographic imaging.

A holographic imaging system based on reconfigurable time-frequency division multiplexing metasurface (RTFDMM) has been designed, in an attempt to address the problems of insufficient flexibility, low signal-to-noise ratio (SNR), and low data of traditional metasurface imaging devices. The modified Gerchberg-Saxton (MGS) algorithm in the front end of this system has been proposed to calculate the phase distribution required by the diffraction metasurface at the back end. The 1-bit low loss reconfigurable metasurface has been desiged in X-band. To obtain the best imaging results, the appropriate ranges of imazging distance, pixel size and resolution ratio are given by adjusting the phase distribution of metasurface. Based on the MGS algorithm and the 1-bit metasurface, the high-quality imaging system has been successfully established through the time-frequency division multiplexing (TFDM) technology. The high SNR imaging can be generated with the expansion of the time domain, while the high data imaging can be yielded with the quantization of the frequency domain. The proof-of-concept has demonstrated that the high data, high SNR, and high flexibility of the RTFDMM are critical technologies for the advancement of detection imaging equipment. Therefore, there are great possibilities for RTFDMM holographic imaging system to be applied in the intelligent detection platform in the future.

Line scanning mechanical streak camera for phosphorescence lifetime imaging.

Phosphorescence lifetime measurement holds great importance in life sciences and material sciences. Due to the long lifetime of phosphorescence emission, conventional approaches based on point scanning time-domain recording suffer from long recording time and low signal-to-noise ratio (SNR). To overcome these difficulties, we developed a line scanning mechanical streak camera for parallel and high SNR imaging. This design offers three key advantages. First, hundreds to thousands of pixels can be recorded simultaneously at high throughput. Second, hundreds of excitation can be accumulated on a single camera frame and read out at once with high quantum efficiency (QE) and low read noise. Third, the system is very simple, only requiring a camera and a scanner. Using a confocal line scanning configuration, we imaged samples of various lifetime ranging from tens of nanoseconds to hundreds of microseconds, which demonstrated the versatility and advantages of this method.

Long working distance high resolution reflective sample imaging via structured embedded speckle illumination

Imaging beyond the diffraction limit at longer working distances using enhanced microscopic configurations has always been a challenge for biological and engineering samples. Even though multiple techniques have been widely used for sub-diffraction limit resolution imaging, the achievable resolution was relying on the use of objective lenses with a high numerical aperture (NA). In the case of engineering samples, in addition to sustaining higher resolutions at large working distances, improving the signal-to-noise ratio (SNR) is also critical. In this context, we propose and demonstrate a concept for high-resolution imaging at large working distances, termed as structured illumination embedded speckle microscopy. An imaging resolution of ~ 310 ± 5 nm was achieved with a microscope objective (0.55 NA; 50X) having 11 mm long working distance using a Siemen's star as the test sample. The demonstrated microscopy is therefore envisaged for engineering applications that demands high-resolution, high SNR imaging at long working distances.

Reducing the dark current of cuprous oxide/Au schottky photodetector for high signal-to-noise ratio imaging

Photodetectors (PDs) as image sensors have been widely used in imaging system due to their outstanding photosensitivity. The improvement of imaging quality (signal-to-noise ratio (SNR)) can be realized by reducing the dark current of PDs. Conventionally, interfacial engineering can effectively suppress the dark current of PDs. Nevertheless, these techniques are hard to be applied in practical imaging systems owing to their complicated process. In this work, we proposed a facile method to reduce the dark current of Cu2O/Au Schottky PDs, and further demonstrated its application in high SNR imaging system. By applying a small external bias of −120 μV, the dark current of PDs decreases from 27 nA to 0.6 nA, with 4023% improvements of ON/OFF ratio. Additonaly, a model based on free carriers generated by rich trap-state and thermal excitation under asymmetric internal electric field was proposed to understand this phenomenon. Finally, a high-resolution image with high SNR (48 dB) was acquired, which is close to that of commercial Si-CDD and CMOS. Our results provide a convenient way to reduce the dark current and improve the image quality, also suggest Cu2O is potentially an attractive candidate to be applied in optical imaging applications.

A High Visibility and SNR Image From One Single-Shot Low-Light Image.

Achieving high visibility and high signal-to-noise ratio (SNR) from a single-shot image captured in low-light environments is an under-constrained problem. To cope with this issue, the intrinsic relationship between the image domain and the radiance domain is first established based on the human visual model, the atmospheric scattering model, and the camera imaging model, and the ideal exposure is derived. Using the illumination-reflection-noise prior, a new convex optimization by employed gradient constraint and the Krisch operator is then presented to estimate the noise-reduced illumination and reflection components. A high SNR image in the optimal exposure is generated in radiance domain, which is finally inversely mapped to obtain a high SNR image in image domain. Experimental results in subjective and objective tests show that the proposed algorithm has a high SNR and pleasant perception in comparison with the state-of-the-art methods.

A Novel Flexible Electrotextile 3T MRI RF Coil Array for Carotid Artery Imaging: Design, Characterization, and Prototyping

Magnetic resonance imaging (MRI) is one of the most powerful imaging modality in clinics and is essential for the diagnosis of strokes through carotid artery imaging. The limiting factor for high-quality MRI is the signal-to-noise ratio (SNR) performance of the radio frequency (RF) coils. The current RF surface coils, however, are made of rigid or semiflexible materials with very limited bending properties. As a result, their SNR is limited because they cannot be placed very close to the imaging area, thus receiving noises from parts of the human body, which are not intended to be imaged. Taking advantage of the computerized embroidery and laser cutting technology, in this paper, we utilize electrotextile to design, fabricate, and measure multilayer RF coil array system for 3 Tesla (3T) MRI to improve the SNR performance. The proposed RF coil array system provides an ergonomic and high-performance solution to the 3T MRI systems. A roadmap to systematically design electrotextile RF coil arrays is proposed. RF coil array is characterized to have the accurate resonant frequency, good impedance matching, and low mutual coupling. In addition, magnetic field distribution, bending effects, and human body effects are also discussed. A systematic method to characterize the performance of the electrotextile pattern is studied and used to assist the development and performance characterization. Finally, the high resolution and high SNR images of various kinds of phantoms are obtained using the University of California at Los Angeles (UCLA) Antenna Lab electrotextile coil array after its integration with the 3T MRI scanners at UCLA David Geffen School of Medicine Translational Research Imaging Center. Compared with the conventional surface coil, more than 10 dB SNR increase is observed at the depth of 0.5 cm and 3 dB increase at the depth of 3 cm.

Imaging DNA Equilibrated onto Mica in Liquid Using Biochemically Relevant Deposition Conditions.

For over 25 years, imaging of DNA by atomic force microscopy has been intensely pursued. Ideally, such images are then used to probe the physical properties of DNA and characterize protein-DNA interactions. The atomic flatness of mica makes it the preferred substrate for high signal-to-noise ratio (SNR) imaging, but the negative charge of mica and DNA hinders deposition. Traditional methods for imaging DNA and protein-DNA complexes in liquid have drawbacks: DNA conformations with an anomalous persistence length ( p), low SNR, and/or ionic deposition conditions detrimental to preserving protein-DNA interactions. Here, we developed a process to bind DNA to mica in a buffer containing both MgCl2 and KCl that resulted in high SNR images of equilibrated DNA in liquid. Achieving an equilibrated 2D configuration ( i. e., p = 50 nm) not only implied a minimally perturbative binding process but also improved data quality and quantity because the DNA's configuration was more extended. In comparison to a purely NiCl2-based protocol, we showed that an 8-fold larger fraction (90%) of 680-nm-long DNA molecules could be quantified. High-resolution images of select equilibrated molecules revealed the right-handed structure of DNA with a helical pitch of 3.5 nm. Deposition and imaging of DNA was achieved over a wide range of monovalent and divalent ionic conditions, including a buffer containing 50 mM KCl and 3 mM MgCl2. Finally, we imaged two protein-DNA complexes using this protocol: a restriction enzyme bound to DNA and a small three-nucleosome array. We expect such deposition of protein-DNA complexes at biochemically relevant ionic conditions will facilitate biophysical insights derived from imaging diverse protein-DNA complexes.

The Influence for Image Quality of Diffusion Weighted Image by Gradient Coil Systems

The purpose of this study was to evaluate the influence for image quality of diffusion weighted image (DWI) by gradient coil systems (two single gradient systems and a dual gradient system). We obtained DWIs of a phantom and three volunteer brains, changing gradient coil systems and echo time (TE) from configurable shortest TE to 130 ms. Image quality of DWI was evaluated by signal to noise ratio (SNR), image distortion, susceptibility artifact, and visual evaluation. SNR of dual gradient system and configurable shortest TE was the highest in phantom study, but there was no difference for SNR of volunteer brain images by each gradient coil system in visual evaluation. Image distortion of single gradient system with low gradient amplitude was the worst in phantom study, and the score of visual evaluation in susceptibility artifact was significantly lower than other gradient coil systems. Dual gradient system was low influence to image distortion and susceptibility artifact. In conclusion, using dual gradient system and configurable shortest TE is recommended for less distortion, low susceptibility artifact, and high SNR image.

How to Improve the Conspicuity of Breast Tumors on Computed High b-value Diffusion-weighted Imaging.

Purpose:The aim of this study was to compare the tumor conspicuity on actual measured diffusion-weighted images (aDWIs) and computed DWI (cDWI) of human breast tumors and to examine, by use of a phantom, whether cDWI improves their conspicuity.Materials and Methods:We acquired DWIs (b-value 0, 700, 1400, 2100, 2800, and 3500 s/mm2) of 148 women with breast tumors. cDWIs with b-values of 1400, 2100, 2800, and 3500 s/mm2 were calculated from aDWI scans where b = 0 and 700 s/mm2; the tumor signal-to-noise ratio (SNR) was compared at each b-value. We also subjected a phantom harboring a breast tumor and mammary glands to DWI. For reference we used two models. The model with b = 0, 1000, 1500, 2000, 2500, and 3000 s/mm2 was our multiple b-value model. In the single b-value model, we applied b = 0 and 1000 s/mm2 and changed the number of excitations (NEX). cDWIs were generated at b = 0 and 1000 and used to compare the SNR, the contrast ratio (CR), and the contrast-to-noise ratio (CNR).Results:In the phantom study, the CNR of cDWI generated from high SNR images obtained at lower b-values and a high NEX was outperformed aDWI. However, the CR and CNR on cDWI obtained using the same scanning parameters were inferior to aDWI scans. Similarly, in the clinical study, breast tumor conspicuity was worse on high b-value cDWIs than aDWIs.Conclusion:To improve tumor conspicuity on cDWI, the quality of the source images must be improved. It may easily cause inferior conspicuity to aDWIs if high b-value cDWIs were generated from insufficient SNR images.

Development of Correction for Signal-to-Noise Ratio Using a T2* With Improved Phase Method.

This study aims to improve the signal-to-noise ratio (SNR) of the phase image focusing T2 and to develop an improved phase (iPhase) image acquired high SNR. The iPhase images of phantom and brain were acquired with multi-echo spoiled gradient-echo. The phantom component was a gadopentetate dimeglumine (Gd-DTPA) solution made of different concentrations (0.1, 0.5, and 1 wt%) and Gd-DTPA (0.1, 0.5, and 1 wt%) with agar (1.0 wt%). We applied the iPhase image to susceptibility weighed image (SWI) and evaluated SNR of SWI. In phantom study, SNRs of conventional SWI at each sample were 19.8, 15.7, 7.4, 20.0, 17.4, and 27.3, respectively. Signal-to-noise ratios of SWI derived from iPhase method were 29.5, 33.7, 21.7, 28.5, 24.3, and 14.7, respectively. Then, the SNR showed an improvement of 196% at maximum (for the Gd-DTPA 1 wt% sample). In healthy volunteer study, SWI derived from iPhase method had the good contrast between white matter and gray matter. The iPhase image was able to improve the phase SNR. Moreover, iPhase method makes it possible to obtain a high SNR image when applying to SWI.

High-speed and high-SNR photoacoustic microscopy based on a galvanometer mirror in non-conducting liquid.

Optical-resolution photoacoustic microscopy (OR-PAM), a promising microscopic imaging technique with high ultrasound resolution and superior optical sensitivity, can provide anatomical, functional, and molecular information at scales ranging from the microvasculature to single red blood cells. In particular, real-time OR-PAM imaging with a high signal-to-noise ratio (SNR) is a prerequisite for widespread use in preclinical and clinical applications. Although several technical approaches have been pursued to simultaneously improve the imaging speed and SNR of OR-PAM, they are bulky, complex, not sensitive, and/or not actually real-time. In this paper, we demonstrate a simple and novel OR-PAM technique which is based on a typical galvanometer immersed in non-conducting liquid. Using an opto-ultrasound combiner, this OR-PAM system achieves a high SNR and fast imaging speed. It takes only 2 seconds to acquire a volumetric image with a wide field of view (FOV) of 4 × 8 mm2 along the X and Y axes, respectively. The measured lateral and axial resolutions are 6.0 and 37.7 μm, respectively. Finally, as a demonstration of the system’s capability, we successfully imaged the microvasculature in a mouse ear in vivo. Our new method will contribute substantially to the popularization and commercialization of OR-PAM in various preclinical and clinical applications.

Multimode intravascular RF coil for MRI‐guided interventions

To demonstrate the feasibility of using a single intravascular radiofrequency (RF) probe connected to the external magnetic resonance imaging (MRI) system via a single coaxial cable to perform active tip tracking and catheter visualization and high signal-to-noise ratio (SNR) intravascular imaging. A multimode intravascular RF coil was constructed on a 6F balloon catheter and interfaced to a 1.5T MRI scanner via a decoupling circuit. Bench measurements of coil impedances were followed by imaging experiments in saline and phantoms. The multimode coil behaves as an inductively coupled transmit coil. The forward-looking capability of 6 mm was measured. A greater than 3-fold increase in SNR compared to conventional imaging using optimized external coil was demonstrated. Simultaneous active tip tracking and catheter visualization was demonstrated. It is feasible to perform 1) active tip tracking, 2) catheter visualization, and 3) high SNR imaging using a single multimode intravascular RF coil that is connected to the external system via a single coaxial cable.

Accuracy of spectrum estimate in fluorescence spectral microscopy with spectral filters

We establish the accuracy of the spectrum that is estimated with an inexpensive fluorescence spectral microscope utilizing a small set of spectral filters [Soriano et al, Opt. Exp. 10, 1458–1464 (2002)]. The spectrum at an arbitrary image location of the fluorescent sample is estimated as a linear superposition of basis spectra that are derived by singular value decomposition (SVD) or principal component analysis (PCA) from a spectral library of fluorescence spectra. Estimation performance is analyzed as a function of library statistics, filter selection and sequencing, minimum negativity constraint and signal to noise ratio (SNR) of fluorescence image. We consider image SNR degradations that arise from weakening of image intensity, additive Gaussian noise, intensity-dependent Poisson noise and quantization errors. The recovery of specific spectral features like spectral resolution, general similarity and peak alignments, is assessed using Linfoot’s criteria of fidelity, structural content, and correlation. We found that estimation with SVD basis spectra is more robust against image noise than that with PCA basis spectra. However for high SNR images, accurate estimation is achieved more quickly with PCA basis spectra and with better response to the application of minimum negativity constraint.