Proposed Imaging System Research Articles

Digital Radiography with a Consumer Camera: Image Denoising and Deblurring

Projection radiography is the most popular medical imaging modality due to its simple design and ease of use. To maintain quality, direct flat-panel detectors must be used to collect patient images, thereby providing a digital radiography (DR) imaging system. In this paper, we investigate an imaging system utilizing a DSLR camera to capture images from a scintillator illuminated by X-rays passing through the object to be imaged. However, maintaining the quality of the image from the proposed system is difficult since it contains impulsive-style noise, and blur varies based on distance. To get rid of unwanted radiographic impulsive noise, we use a statistical-based impulsive noise removal method. To handle the blurring issue in our proposed imaging system, we first use a systematic method to estimate the X-ray source and detector point spread functions (PSFs) from the radiographic image. The PSFs are then used in a non-blind deconvolution algorithm to deblur the image. Experiments on a variety of DR images show that with the proposed denoising and deblurring approaches, our imaging system can provide DR images with fine detail, and it can potentially be used for basic radiography.

Computational Three-Dimensional Imaging System via Diffraction Grating Imaging with Multiple Wavelengths.

This paper describes a computational 3-D imaging system based on diffraction grating imaging with laser sources of multiple wavelengths. It was proven that a diffraction grating imaging system works well as a 3-D imaging system in our previous studies. The diffraction grating imaging system has advantages such as no spherical aberration and a low-cost system, compared with the well-known 3-D imaging systems based on a lens array or a camera array. However, a diffraction grating imaging system still suffers from noises, artifacts, and blurring due to the diffraction nature and illumination of single wavelength lasers. In this paper, we propose a diffraction grating imaging system with multiple wavelengths to overcome these problems. The proposed imaging system can produce multiple volumes through multiple laser illuminators with different wavelengths. Integration of these volumes can reduce noises, artifacts, and blurring in grating imaging since the original signals of 3-D objects inside these volumes are integrated by our computational reconstruction method. To apply the multiple wavelength system to a diffraction grating imaging system efficiently, we analyze the effects on the system parameters such as spatial periods and parallax angles for different wavelengths. A computational 3-D imaging system based on the analysis is proposed to enhance the image quality in diffraction grating imaging. Optical experiments with three-wavelength lasers are conducted to evaluate the proposed system. The results indicate that our diffraction grating imaging system is superior to the existing method.

Fluorescence/photoacoustic imaging-guided nanomaterials for highly efficient cancer theragnostic agent

Imaging modalities combined with a multimodal nanocomposite contrast agent hold great potential for significant contributions in the biomedical field. Among modern imaging techniques, photoacoustic (PA) and fluorescence (FL) imaging gained much attention due to their non-invasive feature and the mutually supportive characteristic in terms of spatial resolution, penetration depth, imaging sensitivity, and speed. In this present study, we synthesized IR783 conjugated chitosan–polypyrrole nanocomposites (IR-CS–PPy NCs) as a theragnostic agent used for FL/PA dual-modal imaging. A customized FL and photoacoustic imaging system was constructed to perform required imaging experiments and create high-contrast images. The proposed nanocomposites were confirmed to have great biosafety, essentially a near-infrared (NIR) absorbance property with enhanced photostability. The in vitro photothermal results indicate the high-efficiency MDA-MB-231 breast cancer cell ablation ability of IR-CS–PPy NCs under 808 nm NIR laser irradiation. The in vivo PTT study revealed the complete destruction of the tumor tissues with IR-CS–PPy NCs without further recurrence. The in vitro and in vivo results suggest that the demonstrated nanocomposites, together with the proposed imaging systems could be an effective theragnostic agent for imaging-guided cancer treatment.

Fast, Robust, and Low-Cost Microwave Imaging of Multiple Non-Metallic Pipes

The use of non-metallic pipes and composite components that are low-cost, durable, light-weight, and resilient to corrosion is growing rapidly in various industrial sectors such as oil and gas industries in the form of non-metallic composite pipes. While these components are still prone to damages, traditional non-destructive testing (NDT) techniques such as eddy current technique and magnetic flux leakage technique cannot be utilized for inspection of these components. Microwave imaging can fill this gap as a favorable technique to perform inspection of non-metallic pipes. Holographic microwave imaging techniques are fast and robust and have been successfully employed in applications such as airport security screening and underground imaging. Here, we extend the use of holographic microwave imaging to inspection of multiple concentric pipes. To increase the speed of data acquisition, we utilize antenna arrays along the azimuthal direction in a cylindrical setup. A parametric study and demonstration of the performance of the proposed imaging system will be provided.

Bionic Birdlike Imaging Using a Multi-Hyperuniform LED Array.

Digital cameras obtain color information of the scene using a chromatic filter, usually a Bayer filter, overlaid on a pixelated detector. However, the periodic arrangement of both the filter array and the detector array introduces frequency aliasing in sampling and color misregistration during demosaicking process which causes degradation of image quality. Inspired by the biological structure of the avian retinas, we developed a chromatic LED array which has a geometric arrangement of multi-hyperuniformity, which exhibits an irregularity on small-length scales but a quasi-uniformity on large scales, to suppress frequency aliasing and color misregistration in full color image retrieval. Experiments were performed with a single-pixel imaging system using the multi-hyperuniform chromatic LED array to provide structured illumination, and 208 fps frame rate was achieved at 32 × 32 pixel resolution. By comparing the experimental results with the images captured with a conventional digital camera, it has been demonstrated that the proposed imaging system forms images with less chromatic moiré patterns and color misregistration artifacts. The concept proposed verified here could provide insights for the design and the manufacturing of future bionic imaging sensors.

Automated monitoring and analyses of honey bee pollen foraging behavior using a deep learning-based imaging system

Pollen foraging efficiency provides vital information for the behavioral research on honey bees. The pollen production of beehives can be measured by manually weighing the pollen collected from pollen traps. For long-term pollen foraging monitoring, this approach is both inefficient and laborious. This study presents an efficient method for automatically monitoring the pollen foraging behavior and environmental conditions through an embedded imaging system. The imaging system uses an off-the-shelf camera installed at the beehive entrance to acquire video streams that are processed using the developed image processing algorithm. A lightweight real-time object detection and deep learning-based classification model, supported by an object tracking algorithm, was trained for counting and recognizing honey bee into pollen or non-pollen bearing class. The F1-score was 0.94 for pollen and non-pollen bearing honey bee recognition, and the precision and recall values were 0.91 and 0.99, respectively. For foraging trip counting algorithm, the mean average percent errors of the pollen bearing honey bee count and the total incoming honey bee count were 8.45 ± 2.72% and 10.55 ± 2.10%, respectively. An experiment was performed to test the performance of the imaging system in continuous monitoring of honey bee pollen foraging behavior as well as to investigate the effect caused by weather factors. The incoming and outgoing honey bee count were recorded and used to calculate indices based on the hourly and daily recorded counts for further analyses. The experimental results and analyses revealed that the daily pollen foraging trip ratio was 24.5 ± 3.5%; a single beehive collected about 49.1 ± 11.0 g of pollen per day. The pollen foraging trip count increased with increasing temperature and light intensity, and decreased with increasing relative humidity, rain level and wind speed. A significant reduction of pollen foraging activities was observed in heavy rainfall or gentle breeze conditions. This study not only quantitatively presents the effect of environmental factors on pollen foraging behavior, but also demonstrates the efficacy of the proposed imaging system. The automated imaging system can be applied as an efficient and reliable tool for researchers to gain deeper insights into honey bee foraging behavior, and help beekeepers achieve beehive management.

Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants

The use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to build an imaging system with high-quality results at a low cost. Useful comparative information for existing imaging systems and their improvements is also limited, making it challenging for researchers to make data-based selections. The objective of this study is to explore the possible solutions to address these issues. We introduce two novel systems for plants of various sizes, as well as a pipeline to generate high-quality 3D point clouds and meshes. The higher accuracy and efficiency of the proposed systems make it a potentially valuable tool for enhancing high-throughput phenotyping by integrating 3D traits for increased resolution and measuring traits that are not amenable to 2D imaging approaches. The study shows that the phenotype traits derived from the 3D models are highly correlated with manually measured phenotypic traits (R2 > 0.91). Moreover, we present a systematic analysis of different settings of the imaging systems and a comparison with the traditional system, which provide recommendations for plant scientists to improve the accuracy of 3D construction. In summary, our proposed imaging systems are suggested for 3D reconstruction of plants. Moreover, the analysis results of the different settings in this paper can be used for designing new customized imaging systems and improving their accuracy.

Super-Resolution Photoacoustic Microscopy Using Structured-Illumination.

A novel super-resolution volumetric photoacoustic microscopy, based on the theory of structured-illumination, is proposed in this paper. The structured-illumination will be introduced in order to surpass the diffraction limit in a photoacoustic microscopy (PAM) structure. Through optical excitation of the targeted object with a sinusoidal spatial fringe pattern, the object's frequency spectrum is forced to shift in the spatial frequency domain. The shifting in the desired direction leads to the passage of the high-frequency contents of the object through the passband of the acoustic diffraction frequency response. Finally, combining the low-frequency image with the high-frequency parts in four regular orientations in the spatial frequency domain is equivalent to imaging the targeted object with an imaging system of two-fold bandwidth and thus half lateral resolution. In order to obtain the image of out-of-focus regions and improve the lateral resolution outside the focal region of a PAM imaging system, Fourier-domain reconstruction algorithm based on the synthetic aperture focusing technique (SAFT) using the virtual detector concept is utilized for reduction in the required computational load and time. The performance of the proposed imaging system is validated with in vivo and ex vivo targets. The experimental results obtained from several tungsten filaments in the depth range of 1.2 mm, show an improvement of -6 dB lateral resolution from 55- [Formula: see text] to 25- [Formula: see text] and also an improvement of signal-to-noise ratio (SNR) from 16-22 dB to 27-33 dB in the proposed system.

Quantitative analysis and optimization design of the segmented planar integrated optical imaging system based on an inhomogeneous multistage sampling lens array.

The non-uniformity of the lens array in the segmented planar integrated optical imaging system has not been studied. We design an inhomogeneous multistage sampling lens array based on a hierarchical multistage sampling lens array of the segmented planar integrated optical imaging system by changing the radius of the lenslet for frequency-selective sampling to optimize the design of the UV spatial frequency distribution. The signal transfer model of the proposed imaging system was established considering the radius of the lenslet and key waveguide parameters. Simulation results show that the proposed system produces better imaging quality owing to the selective sampling of frequency. Compared with the homogeneous multistage sampling lens array (radius of 1.8 mm), the optimal radius parameters of the inhomogeneous multistage sampling lens array are given for the same longest lens array length. Detailed calculations of the parameters of the waveguide connected to the lens array were performed. Our results provide a theoretical basis for the optimal design and process of a new segmented planar integrated optical imaging system.

LED-based compressive spectral-temporal imaging.

A compressive spectral-temporal imaging system is reported. A multi-spectral light-emitting diode array is used for target illumination and spectral modulation, while a digital micro-mirror device (DMD) encodes the spatial and temporal frames. Several encoded video frames are captured in a snapshot of an integrating focal plane array (FPA). A high-frame-rate spectral video is reconstructed from the sequence of compressed measurements captured by the grayscale low-frame-rate camera. The imaging system is optimized through the design of the DMD patterns based on the forward model. Laboratory implementation is conducted to validate the performance of the proposed imaging system. We experimentally demonstrate the video acquisition with eight spectral bands and six temporal frames per FPA snapshot, and thus a 256 × 256 × 8 × 6 4D cube is reconstructed from a single 2D measurement.

Multi-Physical Parameter Cross-Sectional Imaging of Quantitative Phase and Fluorescence by Integrated Multimodal Microscopy

Integrated multimodal cross-sectional or volumetric imaging techniques give us fruitful information to understand the behavior or status of target objects such as biological samples. Most of the reported systems for this purpose are either time consuming due to scanning or use additional reference beams such as in interferometry. Therefore, fast, simple, highly efficient, and powerful multimodal imaging systems that can perform cross-sectional imaging with simple algorithms are worth to be investigated. In this paper, a multimodal technique for cross-sectional quantitative phase and fluorescence imaging with computational microscopy is presented. We combine cross-sectional fluorescence and quantitative phase imaging by using the transport of intensity equation (TIE) and numerical wave propagation. The amplitude and phase of the fluorescence light wave with partially spatial coherence are obtained from three defocused intensity patterns. The proposed hybrid imaging system is simple, compact, and non-iterative. We present experimental results of microbeads and fluorescent protein-labeled living cells of the moss Physcomitrella patens to demonstrate the performance of the proposed imaging system.

Compressive Spectral Imaging Via Virtual Side Information

In recent years there has been an increasing interest in compressive imaging devices that capture spectral images with high spatial and spectral resolution with as few as a single snapshot. Nonetheless, there exists an intrinsic trade-off between spatial and spectral resolution which degrades one at the expense of the other. To alleviate this, state-of-art systems have relied on multiple snapshots attained via dynamically programmable spatial light modulators (SLM), or on side information from a second sensor attained via beam-splitters or stereo setups, which suffer from occlusion and demand registration tasks. This work proposes a compressive snapshot spectral imaging architecture that builds on the ideas of side information, but relies on a single image sensor. Specifically, we propose to split the incoming light into two paths, such as in a conventional interferometer, with one path dispersing the coded light, while the other just relaying it, so as to multiplex a traditional coded-and-dispersed measurement with a modulated grayscale version of the 3D cube in the image sensor. We have coined the latter, virtual side information. The proposed optical system is versatile in the sense that it can move from a fully-encoding system, to a spatially modulated grayscale camera, by switching/blocking the splitting response of the beam-splitters. Furthermore, we propose a computational algorithm to recover the underlying spectral cube exploiting the high spatial resolution provided by the virtual side information. We demonstrate through simulations from over fifty spectral images, and via an experimental proof-of-concept implementation, that the proposed imaging system together with the computational algorithm represents an efficient alternative to acquire spectral images without relying on additional sensors.

Objective evaluation of fabric pilling based on multi-view stereo vision

Fabric pilling evaluation is very important for the quality control of textile industry. Traditional image analysis based methods have the disadvantages of 2 D imaging and color sensitivity, this paper presents a new method based on stereo vision to solve the problem of 3 D imaging of fabric pilling. One set of self-developed mobile camera system is established to capture a group of images for the 3 D reconstruction of the fabric surface, the point cloud model of the fabric surface is generated by the self-developed stereo vision algorithm, including structure from motion (SFM) and patch-based multi-view stereo (PMVS) algorithm. One 2 D gray-scale image is obtained from the 3 D point cloud model by mapping to the 2 D image plane, which contains the depth information of fabric pilling. The segmentation of fabric pilling could be done by accurate positioning of edge detection, adaptive thresholding and morphological analysis. Four feature parameters including pilling number, pilling area, pilling density and coverage ratio are extracted for the determination of fabric pilling grade objectively. Experimental results show that the new developed system and method is effective and reliable for the fabric pilling evaluation, which is consistent with the subjective pilling evaluation. It is workable for the color printed or yarn dyed fabrics, the proposed imaging system could be a good solution for the digital intelligent quality control of textile products.

One-shot color mapping imaging system of light direction extracted from a surface BRDF

The bidirectional reflectance distribution function (BRDF) describes several features of a material surface. A one-shot imaging system is proposed here to obtain an in-plane color mapping of light direction corresponding to surface BRDF distribution. Measurement of a surface inclination angle distribution and detection of microstructure on material surfaces are shown to be attainable by the proposed imaging system.

Holographic Near-Field Microwave Imaging With Antenna Arrays in a Cylindrical Setup

Holographic microwave imaging is fast and robust and it has been adapted for near-field applications such as biomedical imaging and nondestructive testing. While the imaging technique is fast, synthesizing a 2-D aperture by mechanical scanning of the antennas takes time. Here, antenna arrays are used to expedite data acquisition along the azimuthal direction in a cylindrical holographic near-field microwave imaging setup. To deal with the limited and nonuniform samples along the azimuthal direction, three holographic imaging approaches are evaluated, in which, we use interpolation, uniform or nonuniform discrete Fourier transform (DFT), standardized low-resolution brain electromagnetic tomography (sLORETA), and exact low-resolution brain electromagnetic tomography (eLORETA). Besides, to make the system low-cost and portable, off-the-shelf components are used to construct a data acquisition system replacing the vector network analyzers. Simulation and experimental studies are conducted to validate the performance of the proposed imaging system. Structural similarity (SSIM) index is used to assess the quality of the reconstructed images.

An Acquisition Method for Visible and Near Infrared Images from Single CMYG Color Filter Array-Based Sensor.

Near-infrared (NIR) images are very useful in many image processing applications, including banknote recognition, vein detection, and surveillance, to name a few. To acquire the NIR image together with visible range signals, an imaging device should be able to simultaneously capture NIR and visible range images. An implementation of such a system having separate sensors for NIR and visible light has practical shortcomings due to its size and hardware cost. To overcome this, a single sensor-based acquisition method is investigated in this paper. The proposed imaging system is equipped with a conventional color filter array of cyan, magenta, yellow, and green, and achieves signal separation by applying a proposed separation matrix which is derived by mathematical modeling of the signal acquisition structure. The elements of the separation matrix are calculated through color space conversion and experimental data. Subsequently, an additional denoising process is implemented to enhance the quality of the separated images. Experimental results show that the proposed method successfully separates the acquired mixed image of visible and near-infrared signals into individual red, green, and blue (RGB) and NIR images. The separation performance of the proposed method is compared to that of related work in terms of the average peak-signal-to-noise-ratio (PSNR) and color distance. The proposed method attains average PSNR value of 37.04 and 33.29 dB, respectively for the separated RGB and NIR images, which is respectively 6.72 and 2.55 dB higher than the work used for comparison.

A versatile 4D capacitive imaging array: a touchless skin and an obstacle-avoidance sensor for robotic applications

There are growing interests in the use of robots in collaborative environments with humans or other intelligent machines. Sensing the environment for which the robot is operating can be done in many ways, generally guided by skin-like sensors. Some of the skins are inspired by natural sensing in humans or other species. As humans, we use many of our senses, such as version, hearing, smell, and touch, to move around by avoiding colliding with other humans or objects. Different from humans, many other mammals also use whiskers as an additional sensor to help navigate around. In this paper, we demonstrate a touchless capacitive imaging-based sensor in the situation where the obstacles are in close vicinity to the robot. The proposed imaging system can sense the changes in areas near to the skin-like sensors by measuring the capacitances between the array of electrodes. A 4D sensing approach has been developed with the spatiotemporal Total Variation algorithm. The 4D operational mode gives sensors the time awareness that allows for dynamical responses and hence the better control of the robots. Several experiments are conducted to show the skin-like behaviour of this sensor by simulating various scenarios. The sensor shows the excellent ability to detect an object in its vicinity, where the depth is close to half of the planar sensor array size.

Gamma Radiation Imaging System via Variable and Time-Multiplexed Pinhole Arrays.

Biomedical planar imaging using gamma radiation is a very important screening tool for medical diagnostics. Since lens imaging is not available in gamma imaging, the current methods use lead collimator or pinhole techniques to perform imaging. However, due to ineffective utilization of the gamma radiation emitted from the patient’s body and the radioactive dose limit in patients, poor image signal to noise ratio (SNR) and long image capturing time are evident. Furthermore, the resolution is related to the pinhole diameter, thus there is a tradeoff between SNR and resolution. Our objectives are to reduce the radioactive dose given to the patient and to preserve or improve SNR, resolution and capturing time while incorporating three-dimensional capabilities in existing gamma imaging systems. The proposed imaging system is based on super-resolved time-multiplexing methods using both variable and moving pinhole arrays. Simulations were performed both in MATLAB and GEANT4, and gamma single photon emission computed tomography (SPECT) experiments were conducted to support theory and simulations. The proposed method is able to reduce the radioactive dose and image capturing time and to improve SNR and resolution. The results and method enhance the gamma imaging capabilities that exist in current systems, while providing three-dimensional data on the object.

A novel cardiac SPECT system and imaging method

ABSTRACT A novel SPECT model with an elliptical orbit and multiple detectors is proposed for detecting the metabolism of the human heart. Under the structure of the proposed model, the distance between the detector and the patient becomes smaller, which can effectively improve the SNR. The slit-slat collimator is used to collimate the emitted photons. Modified iterative reconstruction algorithm is proposed to reconstruct a small centre field with severe truncation data under the constraints of body contour and total variation (TV). Simulations for the proposed SPECT are implemented to access the image reconstruction quality. The simulation results show that proposed imaging system with appropriate reconstruction methods can provide significant improvements in the spatial resolution and the image quality. The geometric efficiency of the proposed SPECT is about twice that of the conventional SPECT system, but the scanning time is only about one tenth.

Experimental Investigation on Subwavelength Imaging With Temporal–Spatial Random Illuminations

Although significant progress has been achieved in microwave imaging, high/super-resolution imaging remains a long-soughtafter goal. A subwavelength imaging based on temporal-spatial random illuminations is experimentally investigated. Experiments are conducted using a single-frequency array aperture with random phase modulation. The inversion is performed by two different algorithms based on the linear imaging model, and the results show that the location and profile of the object can be successfully reconstructed in a subwavelength scale. In contrast to the broadband meta-assisted imager, an imaging resolution of 0.6λ is achieved while the spectrum/energy efficiency are both guaranteed in the proposed imaging system. These imply the potential of the presented subwavelength imaging method for practical applications.