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Coded aperture imaging (CAI) is a well-established computational imaging technique consisting of two steps, namely the optical recording of an object using a coded mask, followed by a computational reconstruction using a computational algorithm using a pre-recorded point spread function (PSF). In this tutorial, we introduce a simple yet elegant technique called spatial ensemble mapping (SEM) for CAI that allows us to tune the axial resolution post-recording from a single camera shot recorded using an image sensor. The theory, simulation studies, and proof-of-concept experimental studies of SEM-CAI are presented. We believe that the developed approach will benefit microscopy, holography, and smartphone imaging systems. [ABSTRACT FROM AUTHOR]

BackgroundTargeted alpha-particle therapy (TAT) has great promise as a cancer treatment. Arguably the most promising TAT radionuclide that has been proposed is 225 Ac. The development of 225 Ac-based radiopharmaceuticals has been hampered due to the lack of effective means to study the daughter redistribution of these agents in small animals at the preclinical stage.PurposeThe ability to directly image the daughters, namely 221 Fr and 213 Bi, via their gamma-ray emissions would be a boon for preclinical studies. That said, conventional medical imaging modalities, including single photon emission computed tomography (SPECT) based on nonmultiplexed collimation, cannot be employed due to sensitivity limitations.MethodsAs an alternative, we propose the use of both coded aperture and Compton imaging with the former modality suited to the 218-keV gamma-ray emission of 221 Fr and the latter suited to the 440-keV gamma-ray emission of 213 Bi.ResultsThis work includes coded aperture images of 221 Fr and Compton images of 213 Bi in tumor-bearing mice injected with 225 Ac-based radiopharmaceuticals.ConclusionsThese results are the first demonstration of visualizing and quantifying the 225 Ac daughters in small animals through the application of coded aperture and Compton imaging.

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Interferenceless coded aperture correlation holography (I-COACH) is a robust imaging technique for recovering three-dimensional object information using incoherent holography without two-beam interference. In this study, five-dimensional (5D) imaging along 3D space, spectrum and polarization in I-COACH is proposed and experimentally demonstrated for the first time. The proposed technique exploits the polarization-dependent light modulation characteristics of spatial light modulators to record polarization-dependent intensity distributions, which are distinguished by significant blurring between orthogonal polarization states. 5D I-COACH is implemented by inter-connecting all five dimensions in a single frame, and image recovery is attempted from different configurations of recorded point spread intensity distributions and response-to-object intensity distributions along 5D using recently developed deconvolution techniques. The simulation and experimental results confirm the 5D imaging capabilities of I-COACH. The proposed technique can be a useful tool for birefringence microscopy, and functional and structural imaging applications.

The high-dimensional nature of the 4-D light field (LF) poses great challenges in achieving efficient and effective feature embedding, that severely impacts the performance of downstream tasks. To tackle this crucial issue, in contrast to existing methods with empirically-designed architectures, we propose a probabilistic-based feature embedding (PFE), which learns a feature embedding architecture by assembling various low-dimensional convolution patterns in a probability space for fully capturing spatial-angular information. Building upon the proposed PFE, we then leverage the intrinsic linear imaging model of the coded aperture camera to construct a cycle-consistent 4-D LF reconstruction network from coded measurements. Moreover, we incorporate PFE into an iterative optimization framework for 4-D LF denoising. Our extensive experiments demonstrate the significant superiority of our methods on both real-world and synthetic 4-D LF images, both quantitatively and qualitatively, when compared with state-of-the-art methods. The source code will be publicly available at https://github.com/lyuxianqiang/LFCA-CR-NET. [ABSTRACT FROM AUTHOR]

Coded aperture imaging (CAI) is a well-established computational imaging technique consisting of two steps, namely the optical recording of an object using a coded mask, followed by a computational reconstruction using a computational algorithm using a pre-recorded point spread function (PSF). In this tutorial, we introduce a simple yet elegant technique called spatial ensemble mapping (SEM) for CAI that allows us to tune the axial resolution post-recording from a single camera shot recorded using an image sensor. The theory, simulation studies, and proof-of-concept experimental studies of SEM-CAI are presented. We believe that the developed approach will benefit microscopy, holography, and smartphone imaging systems.

Metamaterial-based coded aperture imaging (MCAI) is a forward-looking radar imaging technique based on wavefront modulation. The scattering coefficients of the target can resolve as an ill-posed inverse problem. Data-based deep-learning methods provide an efficient, but expensive, way for target reconstruction. To address the difficulty in collecting paired training data, an untrained deep radar-echo-prior-based MCAI (DMCAI) optimization model is proposed. DMCAI combines the MCAI model with a modified U-Net for predicting radar echo. A joint loss function based on deep-radar echo prior and total variation is utilized to optimize network weights through back-propagation. A target reconstruction strategy by alternatively using the imaginary and real part of the radar echo signal (STAIR) is proposed to solve the DMCAI. It makes the target reconstruction task turn into an estimation from an input image by the U-Net. Then, the optimized weights serve as a parametrization that bridges the input image and the target. The simulation and experimental results demonstrate the effectiveness of the proposed approach under different SNRs or compression measurements. [ABSTRACT FROM AUTHOR]

Background: Modified Uniformly Redundant Array (MURA) Coded Aperture (CA) is a type of mask recently proposed for breast tumor imaging. Such masks have been frequently used in nuclear medicine clinical applications for the past two decades. All CA imaging methods are still limited to planar imaging, with only a few exceptions where they can be used for thin 3D imaging. At present, there is no commercially available SPECT camera that employs CA technology. Materials and Methods: This paper is investigating the proof-of-concept of the MURA CA mask for 3D breast tumor imaging. Such image formation performed well in planar imaging, but it is not fully evaluated for thick sources in 3D imaging. This paper demonstrated the performance of MURA in 3D breast imaging. The proposed imaging system uses a MURA mask and antimask dual reconstruction, and the raw projections are reconstructed using an iterative algorithm, Maximum Likelihood Expectation Maximization (MLEM). Results: The MURA antimask-reconstructed images are summed with mask images to enhance sensitivity, and the resultant image with up to 3 mm lesion diameter can be detected. The reconstructed image quality is measured by plotting profiles and by measuring contrast-to-background ratio, peak-signal-to-noise ratio, and mean square error. Conclusion: The proposed scintigraphy system has successfully reconstructed a breast phantom with a lesion of 3 mm diameter and tumor-to-background ratio of 10:1 using a MURA CA mask. Therefore, MURA 3D scintigraphy can be used to diagnose cancer at an early stage. [ABSTRACT FROM AUTHOR]

Background: Targeted alpha‐particle therapy (TAT) has great promise as a cancer treatment. Arguably the most promising TAT radionuclide that has been proposed is 225Ac. The development of 225Ac‐based radiopharmaceuticals has been hampered due to the lack of effective means to study the daughter redistribution of these agents in small animals at the preclinical stage. Purpose: The ability to directly image the daughters, namely 221Fr and 213Bi, via their gamma‐ray emissions would be a boon for preclinical studies. That said, conventional medical imaging modalities, including single photon emission computed tomography (SPECT) based on nonmultiplexed collimation, cannot be employed due to sensitivity limitations. Methods: As an alternative, we propose the use of both coded aperture and Compton imaging with the former modality suited to the 218‐keV gamma‐ray emission of 221Fr and the latter suited to the 440‐keV gamma‐ray emission of 213Bi. Results: This work includes coded aperture images of 221Fr and Compton images of 213Bi in tumor‐bearing mice injected with 225Ac‐based radiopharmaceuticals. Conclusions: These results are the first demonstration of visualizing and quantifying the 225Ac daughters in small animals through the application of coded aperture and Compton imaging. [ABSTRACT FROM AUTHOR]

Coded aperture 3D imaging techniques have been rapidly evolving in recent years. The two main directions of evolution are in aperture engineering to generate the optimal optical field and in the development of a computational reconstruction method to reconstruct the object's image from the intensity distribution with minimal noise. The goal is to find the ideal aperture–reconstruction method pair, and if not that, to optimize one to match the other for designing an imaging system with the required 3D imaging characteristics. The Lucy–Richardson–Rosen algorithm (LR2A), a recently developed computational reconstruction method, was found to perform better than its predecessors, such as matched filter, inverse filter, phase-only filter, Lucy–Richardson algorithm, and non-linear reconstruction (NLR), for certain apertures when the point spread function (PSF) is a real and symmetric function. For other cases of PSF, NLR performed better than the rest of the methods. In this tutorial, LR2A has been presented as a generalized approach for any optical field when the PSF is known along with MATLAB codes for reconstruction. The common problems and pitfalls in using LR2A have been discussed. Simulation and experimental studies for common optical fields such as spherical, Bessel, vortex beams, and exotic optical fields such as Airy, scattered, and self-rotating beams have been presented. From this study, it can be seen that it is possible to transfer the 3D imaging characteristics from non-imaging-type exotic fields to indirect imaging systems faithfully using LR2A. The application of LR2A to medical images such as colonoscopy images and cone beam computed tomography images with synthetic PSF has been demonstrated. We believe that the tutorial will provide a deeper understanding of computational reconstruction using LR2A. [ABSTRACT FROM AUTHOR]

In recent years, a wide range of hyperspectral imaging systems using coded apertures have been proposed. Many implement compressive sensing to achieve faster acquisition of a hyperspectral data cube, but it is also potentially beneficial to use coded aperture imaging in sensors that capture full-rank (non-compressive) measurements. In this paper we analyse the signal-to-noise ratio for such a sensor, which uses a Hadamard code pattern of slits instead of the single slit of a typical pushbroom imaging spectrometer. We show that the coded slit sensor may have performance advantages in situations where the dominant noise sources do not depend on the signal level; but that where Shot noise dominates a conventional single-slit sensor would be more effective. These results may also have implications for the utility of compressive sensing systems.

Interferenceless coded aperture correlation holography (I-COACH) was recently introduced for recording incoherent holograms without two-wave interference. In I-COACH, the light radiated from an object is modulated by a pseudo-randomly-coded phase mask and recorded as a hologram by a digital camera without interfering with any other beams. The image reconstruction is conducted by correlating the object hologram with the point spread hologram. However, the image reconstructed by the conventional correlation algorithm suffers from serious background noise, which leads to poor imaging quality. In this work, via an effective combination of the speckle correlation and neural network, we propose a high-quality reconstruction strategy based on physics-informed deep learning. Specifically, this method takes the autocorrelation of the speckle image as the input of the network, and switches from establishing a direct mapping between the object and the image into a mapping between the autocorrelations of the two. This method improves the interpretability of neural networks through prior physics knowledge, thereby remedying the data dependence and computational cost. In addition, once a final model is obtained, the image reconstruction can be completed by one camera exposure. Experimental results demonstrate that the background noise can be effectively suppressed, and the resolution of the reconstructed images can be enhanced by three times. [ABSTRACT FROM AUTHOR]

We report the development of a gamma-ray imaging device, named Large-Area Hybrid Gamma Imager (LAHGI), featuring high imaging sensitivity and good imaging resolution over a broad energy range. A hybrid collimation method, which combines mechanical and electronic collimation, is employed for a stable imaging performance based on large-area scintillation detectors for high imaging sensitivity. The system comprises two monolithic position-sensitive NaI(Tl) scintillation detectors with a crystal area of 27 × 27 cm2 and a tungsten coded aperture mask with a modified uniformly redundant array (MURA) pattern. The performance of the system was evaluated under several source conditions. The system showed good imaging resolution (i.e., 6.0–8.9° FWHM) for the entire energy range of 59.5–1330 keV considered in the present study. It also showed very high imaging sensitivity, successfully imaging a 253 μCi 137Cs source located 15 m away in 1 min; this performance is notable considering that the dose rate at the front surface of the system, due to the existence of the 137Cs source, was only 0.003 μSv/h, which corresponds to ∼3% of the background level.

Coded aperture 3D imaging techniques have been rapidly evolving in recent years. The two main directions of evolution are in aperture engineering to generate the optimal optical field and in the development of a computational reconstruction method to reconstruct the object’s image from the intensity distribution with minimal noise. The goal is to find the ideal aperture–reconstruction method pair, and if not that, to optimize one to match the other for designing an imaging system with the required 3D imaging characteristics. The Lucy–Richardson–Rosen algorithm (LR2A), a recently developed computational reconstruction method, was found to perform better than its predecessors, such as matched filter, inverse filter, phase-only filter, Lucy–Richardson algorithm, and non-linear reconstruction (NLR), for certain apertures when the point spread function (PSF) is a real and symmetric function. For other cases of PSF, NLR performed better than the rest of the methods. In this tutorial, LR2A has been presented as a generalized approach for any optical field when the PSF is known along with MATLAB codes for reconstruction. The common problems and pitfalls in using LR2A have been discussed. Simulation and experimental studies for common optical fields such as spherical, Bessel, vortex beams, and exotic optical fields such as Airy, scattered, and self-rotating beams have been presented. From this study, it can be seen that it is possible to transfer the 3D imaging characteristics from non-imaging-type exotic fields to indirect imaging systems faithfully using LR2A. The application of LR2A to medical images such as colonoscopy images and cone beam computed tomography images with synthetic PSF has been demonstrated. We believe that the tutorial will provide a deeper understanding of computational reconstruction using LR2A.

X-ray polarization is a powerful tool for unveiling the anisotropic characteristics of high-energy celestial objects. We present a novel imaging reconstruction method designed for hard X-ray polarimeters employing a Si CMOS sensor and coded apertures, which function as a photoelectron tracker and imaging optics, respectively. Faced with challenges posed by substantial artifacts and background noise in the coded aperture imaging associated with the conventional balanced correlation method, we adopt the Expectation–Maximization (EM) algorithm as the foundation of our imaging reconstruction method. The newly developed imaging reconstruction method is validated with imaging polarimetry and a series of X-ray beam experiments. The method demonstrates the capability to accurately reproduce an extended source comprising multiple segments with distinct polarization degrees. Comparative analysis exhibits a significant enhancement in imaging reconstruction accuracy compared to the balanced correlation method, with the background noise levels reduced to 17%. The outcomes of this study enhance the feasibility of Cube-Sat imaging polarimetry missions in the hard X-ray band, as the combination of Si CMOS sensors and coded apertures is a promising approach for realizing it. [ABSTRACT FROM AUTHOR]

Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object's image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object's image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR isinvestigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed. [ABSTRACT FROM AUTHOR]

Interferenceless coded aperture correlation holography (I-COACH) provides an alternative way for the 3D imaging of spatial incoherent illuminated or fluorescent sample. However, the low imaging signal-to-noise ratio (SNR) is one of the bottlenecks that restrict the application of I-COACH. The limitation is mainly originated from the strong bias level that presents in the recorded holograms. Phase shifting methods were implemented in I-COACH to eliminate the background noise while the multiple-exposures recording mechanism significantly reduces the temporal resolution of the system. In this paper, we proposed a compressive I-COACH imaging method with high reconstruction quality and without the sacrifice of the imaging speed. The 3D holographic image reconstruction was implemented under compressive sensing framework while only one single-exposure object hologram and one point spread hologram are necessary. High quality reconstructions were obtained using the proposed method, even for the down-sampled holograms. The imaging SNR of the I-COACH system was improved by a factor of more than 16.5% when comparing with the imaging SNR obtained by the conventional cross-correlation reconstruction method. The proposed method provides a fast and high-fidelity imaging method that can potentially benefit the imaging through scattering medium, partial aperture imaging, and other fields. [ABSTRACT FROM AUTHOR]

This work reports on the development of a binary pseudo-random test sample optimized to calibrate the MTF of optical microscopes. The sample consists of a number of 1-D and 2-D patterns, with different minimum sizes of spatial artifacts from 300 nm to 2 microns. We describe the mathematical background, fabrication process, data acquisition and analysis procedure to return spatial frequency based instrument calibration. We show that the developed samples satisfy the characteristics of a test standard: functionality, ease of specification and fabrication, reproducibility, and low sensitivity to manufacturing error.

Interferenceless coded aperture correlation holography (I-COACH) was recently introduced for recording incoherent holograms without two-wave interference. In I-COACH, the light radiated from an object is modulated by a pseudo-randomly-coded phase mask and recorded as a hologram by a digital camera without interfering with any other beams. The image reconstruction is conducted by correlating the object hologram with the point spread hologram. However, the image reconstructed by the conventional correlation algorithm suffers from serious background noise, which leads to poor imaging quality. In this work, via an effective combination of the speckle correlation and neural network, we propose a high-quality reconstruction strategy based on physics-informed deep learning. Specifically, this method takes the autocorrelation of the speckle image as the input of the network, and switches from establishing a direct mapping between the object and the image into a mapping between the autocorrelations of the two. This method improves the interpretability of neural networks through prior physics knowledge, thereby remedying the data dependence and computational cost. In addition, once a final model is obtained, the image reconstruction can be completed by one camera exposure. Experimental results demonstrate that the background noise can be effectively suppressed, and the resolution of the reconstructed images can be enhanced by three times.

Indirect-imaging methods involve at least two steps, namely optical recording and computational reconstruction. The optical-recording process uses an optical modulator that transforms the light from the object into a typical intensity distribution. This distribution is numerically processed to reconstruct the object’s image corresponding to different spatial and spectral dimensions. There have been numerous optical-modulation functions and reconstruction methods developed in the past few years for different applications. In most cases, a compatible pair of the optical-modulation function and reconstruction method gives optimal performance. A new reconstruction method, termed nonlinear reconstruction (NLR), was developed in 2017 to reconstruct the object image in the case of optical-scattering modulators. Over the years, it has been revealed that the NLR can reconstruct an object’s image modulated by an axicons, bifocal lenses and even exotic spiral diffractive elements, which generate deterministic optical fields. Apparently, NLR seems to be a universal reconstruction method for indirect imaging. In this review, the performance of NLR isinvestigated for many deterministic and stochastic optical fields. Simulation and experimental results for different cases are presented and discussed.

Digital image devices have been widely applied in many fields, such as individual recognition and remote sensing. The captured image is a degraded image from the latent observation, where the degradation processing is affected by some factors, such as lighting and noise corruption. Specifically, noise is generated in the processing of transmission and compression from the unknown latent observation. Thus, it is essential to use image denoising techniques to remove noise and recover the latent observation from the given degraded image. In this research, a supervised encoder–decoder convolution neural network was used to fix image distortion stemming from the limited accuracy of inverse filter methods (Wiener filter, Lucy–Richardson deconvolution, etc.). Particularly, we will correct image degradation that mainly stems from duplications arising from multiple-pinhole array imaging.

Snapshot compressed sensing (CS) refers to compressive imaging systems in which multiple frames are mapped into a single measurement frame. Each pixel in the acquired frame is a noisy linear mapping of the corresponding pixels in the frames that are combined together. While the problem can be cast as a CS problem, due to the very special structure of the sensing matrix, standard CS theory cannot be employed to study such systems. In this paper, a compression-based framework is employed for theoretical analysis of snapshot CS systems. It is shown that this framework leads to two novel, computationally-efficient and theoretically-analyzable compression-based recovery algorithms. The proposed methods are iterative and employ compression codes to define and impose the structure of the desired signal. Theoretical convergence guarantees are derived for both algorithms. In the simulations, it is shown that, in the cases of both noise-free and noisy measurements, combining the proposed algorithms with a customized video compression code, designed to exploit nonlocal structures of video frames, significantly improves the state-of-the-art performance. [ABSTRACT FROM AUTHOR]

Image enhancement techniques (such as edge and contrast enhancement) are essential for many imaging applications. In incoherent holography techniques such as Fresnel incoherent correlation holography (FINCH), the light from an object is split into two, each of which is modulated differently from one another by two different quadratic phase functions and coherently interfered to generate the hologram. The hologram can be reconstructed via a numerical backpropagation. The edge enhancement procedure in FINCH requires the modulation of one of the beams by a spiral phase element and, upon reconstruction, edge-enhanced images are obtained. An optical technique for edge enhancement in coded aperture imaging (CAI) techniques that does not involve two-beam interference has not been established yet. In this study, we propose and demonstrate an iterative algorithm that can yield from the experimentally recorded point spread function (PSF), a synthetic PSF that can generate edge-enhanced reconstructions when processed with the object hologram. The edge-enhanced reconstructions are subtracted from the original reconstructions to obtain contrast enhancement. The technique has been demonstrated on FINCH and CAI methods with different spectral conditions.

• A new class of INCoherent Hybrid Imaging Systems (INCHIS) have been proposed and demonstrated. • With INCHIS it is possible to tune axial resolution independent of lateral resolution. • For the first time, it is possible to tune axial resolution of recorded pictures and videos using INCHIS. Axial resolving power (ARP) is one of the cornerstones of imaging systems. In conventional imaging systems, changing ARP by changing the numerical aperture affects also lateral resolving power (LRP). It is highly desirable to change ARP independent of LRP. Recently, incoherent digital holography (IDH) techniques were developed using sparse ensembles of Bessel, Airy and self-rotating beams that allow tuning ARP independent of LRP. In the above studies, the ARP was tuned by controlling the randomness which resulted in noisy reconstructions. In this study, we proposed and demonstrated two INCoherent Hybrid Imaging Systems (INCHIS) using a Bessel and spherical beam to change the ARP between the limits of Bessel and spherical beam independent of LRP. The first hybridization technique INCHIS-H1 requires pre-engineering of multifunctional phase masks using a recently developed modified Gerchberg-Saxton algorithm and an active device such as a spatial light modulator. The second hybridization technique INCHIS-H2 can be implemented using both active as well as passive optical elements with lens and axicon functions and the ARP is changed digitally after optical recording. While INCHIS-H1 requires pre-engineering of phase masks to change ARP like any conventional imaging system, the capability in INCHIS-H2 to change ARP post-recording opens a new pathway in imaging technology. Simulation results and proof-of-concept experimental results are presented. A recently developed Lucy-Richardson-Rosen algorithm has been used for image reconstruction for the above cases. We believe that the developed hybridization methods will revolutionize the field of IDH, computational imaging, computer vision and microscopy. [ABSTRACT FROM AUTHOR]

One of the main concerns regarding medical imaging is the danger tissue’s ionizing due to the applied radiation. Many medical procedures are based on this ionizing radiation (such as X-rays and Gamma radiation). This radiation allows the physician to perform diagnosis inside the human body. Still, the main concern is stochastic effects to the DNA, particularly the cause of cancer. The radiation dose endangers not only the patient but also the medical staff, who might be close to the patient and be exposed to this dangerous radiation in a daily manner. This paper presents a novel concept of radiation reduced Computed Tomography (CT) scans. The proposed concept includes two main methods: minification to enhance the energy concertation per pixel and subpixel resolution enhancement, using shifted images, to preserve resolution. The proposed process uses several pinhole masks as the base of the imaging modality. The proposed concept was validated numerically and experimentally and has demonstrated the capability of reducing the radiation efficiency by factor 4, being highly significant to the world of radiology and CT scans. This dose reduction allows a safer imaging process for the patient and the medical staff. This method simplifies the system and improves the obtained image quality. The proposed method can contribute additively to standard existing dose reduction or super-resolution techniques to achieve even better performance.

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.

Formulae for the signal-to-noise ratio (SNR) of Singer product apertures are derived, allowing optimal Singer product apertures to be identified, and the CPU time required to decode them is quantified. This allows a systematic comparison to be made of the performance of Singer product apertures against both conventionally wrapped Singer apertures, and also conventional product apertures such as square uniformly redundant arrays. For very large images, equivalently for images at very high resolution, the SNR of Singer product apertures is asymptotically as good as the best conventional apertures, but Singer product apertures decode faster than any conventional aperture by at least a factor of ten for image sizes up to several megapixels. These theoretical predictions are verified using numerical simulations, demonstrating that coded aperture video is for the first time a realistic possibility. [ABSTRACT FROM AUTHOR]

[Display omitted] • Development of a new CdTe-based compact gamma camera using a Timepix4 readout circuit. • Use of a coded aperture mask collimator for high sensitivity and axial depth resolution. • Monte Carlo simulations showed a sensitivity of 0.2 cps/kBq, a lateral resolution of 1.7 mm and an axial resolution of 7.3 mm. • First experimental tests with a Si Timepix4 detector are reported and compared to Monte Carlo simulations. We designed a prototype compact gamma camera (MediPROBE4) for nuclear medicine tasks, including radio-guided surgery and sentinel lymph node imaging with a 99mTc radiotracer. We performed Monte Carlo (MC) simulations for image performance assessment, and first spectroscopic imaging tests with a 300 μm thick silicon detector. The hand-held camera (1 kg weight) is based on a Timepix4 readout circuit for photon-counting, energy-sensitive, hybrid pixel detectors (24.6 × 28.2 mm2 sensitive area, 55 μm pixel pitch), developed by the Medipix4 Collaboration. The camera design adopts a CdTe detector (1 or 2 mm thick) bump-bonded to a Timepix4 readout chip and a coded aperture collimator with 0.25 mm diameter round holes made of 3D printed 1-mm thick tungsten. Image reconstruction is performed via autocorrelation deconvolution. Geant4 MC simulations showed that, for a 99mTc source in air, at 50 mm source-collimator distance, the estimated collimator sensitivity (4 × 10−4) is 292 times larger than that of a single hole in the mask; the system sensitivity is 0.22 cps/kBq (2 mm CdTe); the lateral spatial resolution is 1.7 mm FWHM. The estimated axial longitudinal resolution is 8.2 mm FWHM at 40 mm distance. First experimental tests with a 300 μm thick Silicon pixel detector bump-bonded to a Timepix4 chip and a high-resolution coded aperture collimator showed time-over-threshold and time-of-arrival capabilities with 241Am and 133Ba gamma-ray sources. MC simulations and validation lab tests showed the expected performance of the MediPROBE4 compact gamma camera for gamma-ray 3D imaging. [ABSTRACT FROM AUTHOR]

• A deep-learning-based interferenceless coded aperture correlation holographic imaging technique (DP-based I-COACH) is developed resulting in the original object reconstruction from a single-shot object-hologram without any point spread hologram priori. • Though the reconstruction is obtained by single-shot object hologram in the DP-based I-COACH, the reconstruction image quality is obviously improved owing to well-trained CNN compared to nonlinear reconstruction or phase filter reconstruction which both relay on the object-hologram and PSF library. • Depth of field has been verified to be extended in our proposal without sacrificing the imaging quality and increasing the complexity of system, which makes the technique possess the potential for imaging thick object or multi 2D-object in a relative large z-axial range simultaneously. In interferenceless coded aperture correlation holography with incoherent illumination(I-COACH), point spread hologram(PSH) is important and it is usually necessary to record the PSH library priori. However, the recording of PSH library is time-consuming and basiclly difficult to obtain ideal PSH. The reconstructions correspondingly suffer from some noise which results from the cross-correlation reconstruction of nonideal PSH and object hologram (OH). Here a deep-learning-based interferenceless coded aperture correlation holographic imaging technique (DP-based I-COACH) is developed, in which the object can be reconstructed directly from a single-shot object hologram (OH) without any point spread hologram priori. In DP-based I-COACH, a convolutional neural network (CNN) composed of five encoders and four decoders which follows the encoder-decoder "U-net" architecture is employed. Different object intensity patterns recorded by single-shot together with their associated ground truth form data pairs, are used to train the CNN. In order to demonstrate the reliability of our proposed method, the imaging performances of our proposal is investigated under different experimental conditions, the reconstruction image quality is obviously improved compared with other reconstruction algorithms. The depth of field extension of our proposal without sacrificing the imaging quality and increasing the complexity of system is also described, which will drive the application of I-COACH in some potential scenarios, such as endoscopic application. [ABSTRACT FROM AUTHOR]

Scintillator-based detectors are among the most commonly used methods for detecting ionizing radiation. Scintillators provide a reliable, cost-effective, and simple way to make large-volume detectors. Furthermore, localizing the position of the interactions in three dimensions within the crystals is useful to a wide array of fields. The most straightforward way of doing this is to pair the crystal with a position-sensitive phototransducer (PT). This allows for measurement of the shape of the light spot at the PT plane. Using this information, various methods exist to localize the gamma-ray interaction in the crystal; however, the position resolution worsens the farther the event occurs from the PT plane. To improve on the localization ability, this work uses an optical coded-aperture shadow mask between the crystal and the PT. The recorded detector response is used in reconstructing the event over the entire depth of the crystal, and the “sharpest” reconstructed image gives an event’s depth. The lateral position is given from the standard coded-aperture image reconstruction. Experimental results obtained by emulating a 26-mm-thick crystal using a thin 1-mm-thick NaI(Tl) crystal and different amounts of light pipe between the crystal and the PT plane achieved \sim 1 to 2-mm resolution in all three dimensions throughout most of the 26-mm-thick crystal. [ABSTRACT FROM PUBLISHER]

The localization of radiation interactions in bulk scintillators is generally limited by the size of the light distribution at the readout surface of the crystal/light-pipe system. By finding the centroid of the light spot, which is typically of order centimeters across, practical single-event localization is limited to ~2 mm/cm of crystal thickness. Similar resolution can also be achieved for the depth of interaction by measuring the size of the light spot. Through the use of near-field coded-aperture techniques applied to the scintillation light, light transport simulations show that for 3-cm-thick crystals, more than a five-fold improvement (millimeter spatial resolution) can be achieved both laterally and in event depth. At the core of the technique is the requirement to resolve the shadow from an optical mask placed in the scintillation light path between the crystal and the readout. In this paper, experimental results are presented that demonstrate the overall concept using a 1D shadow mask, a thin-scintillator crystal and a light pipe of varying thickness to emulate a 2.2-cm-thick crystal. Spatial resolutions of ~1 mm in both depth and transverse to the readout face are obtained over most of the crystal depth. [ABSTRACT FROM AUTHOR]

X-ray phase-contrast imaging (XPCI) holds great promise for medical X-ray imaging with high soft-tissue contrast. Obviating optical elements in the imaging chain, propagation-based XPCI (PB-XPCI) has definite advantages over other XPCI techniques in terms of cost, alignment and scalability. However, it imposes strict requirements on the spatial coherence of the source and the resolution of the detector. In this study, we demonstrate that using a coded X-ray source and sparsity-based reconstruction, we can significantly relax these requirements. Using numerical simulation, we assess the feasibility of our approach and study the effect of system parameters on the reconstructed image. The results are demonstrated with images obtained using a bench-top micro-focus XPCI system. [ABSTRACT FROM AUTHOR]

A novel method of muonic X-ray imaging based on the coded aperture imaging technique is developed. The image quality and detection rate of X-rays can be influenced by the number of detected counts (N D), mask size (thickness t and aperture size d) and sample-to-detector distance (D S D). A figure of merit (F o M) is introduced as an integral and quantitative indicator of these influences. The choice of optimal values of the parameters N D , t , d and D S D is achieved therefore by the comparison of respective F o M values. As compared to the conventional pinhole imaging technique, the coded aperture technique provides slightly better image quality and has a two orders of magnitude higher detection rate. Therefore, the F o M value for the coded aperture imaging technique is higher than that for the pinhole one by a factor not smaller than 1.67. Obtained results demonstrate that the coded aperture imaging technique has significant advantages for the applications for elemental analysis by muonic X-ray measurements. • First simulation study of coded aperture technique in muonic X-ray imaging. • Anti-mask technique is better than only-mask technique in image quality. • Imaging system is effectively optimized using the newly proposed figure of merit. • The coded aperture technique greatly improves detection rate over pinhole imaging. • The dimension resolution is better than 2×2 mm 2 . [ABSTRACT FROM AUTHOR]