Photon-counting Imaging Research Articles

Exoplanet detection in starshade images

A starshade suppresses starlight by a factor of 1011 in the image plane of a telescope, which is crucial for directly imaging Earth-like exoplanets. The state-of-the-art in high-contrast post-processing and signal detection methods was developed specifically for images taken with an internal coronagraph system and focused on the removal of quasi-static speckles. These methods are less useful for starshade images where such speckles are not present. We are dedicated to investigating signal processing methods tailored to work efficiently on starshade images. We describe a signal detection method, the generalized likelihood ratio test (GLRT), for starshade missions and look into three important problems. First, even with the light suppression provided by the starshade, rocky exoplanets are still difficult to detect in reflected light due to their absolute faintness. GLRT can successfully flag these dim planets. Moreover, GLRT provides estimates of the planets’ positions and intensities and the theoretical false alarm rate of the detection. Second, small starshade shape errors, such as a truncated petal tip, can cause artifacts that are hard to distinguish from real planet signals; the detection method can help distinguish planet signals from such artifacts. The third direct imaging problem is that exozodiacal dust degrades detection performance. We develop an iterative GLRT to mitigate the effect of dust on the image. In addition, we provide guidance on how to choose the number of photon counting images to combine into one co-added image before doing detection, which will help utilize the observation time efficiently. All the methods are demonstrated on realistic simulated images.

Calculation of Stopping-Power Ratio from Multiple CT Numbers Using Photon-Counting CT System: Two- and Three-Parameter-Fitting Method.

The two-parameter-fitting method (PFM) is commonly used to calculate the stopping-power ratio (SPR). This study proposes a new formalism: a three-PFM, which can be used in multiple spectral computed tomography (CT). Using a photon-counting CT system, seven rod-shaped samples of aluminium, graphite, and poly(methyl methacrylate) (PMMA), and four types of biological phantom materials were placed in a water-filled sample holder. The X-ray tube voltage and current were set at 150 kV and 40 A respectively, and four CT images were obtained at four threshold settings. A semi-empirical correction method that corrects the difference between the CT values from the photon-counting CT images and theoretical values in each spectral region was also introduced. Both the two- and three-PFMs were used to calculate the effective atomic number and electron density from multiple CT numbers. The mean excitation energy was calculated via parameterisation with the effective atomic number, and the SPR was then calculated from the calculated electron density and mean excitation energy. Then, the SPRs from both methods were compared with the theoretical values. To estimate the noise level of the CT numbers obtained from the photon-counting CT, CT numbers, including noise, were simulated to evaluate the robustness of the aforementioned PFMs. For the aluminium and graphite, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 17.1% and 7.1%, respectively. For the PMMA and biological phantom materials, the maximum relative errors for the SPRs calculated using the two-PFM and three-PFM were 5.5% and 2.0%, respectively. It was concluded that the three-PFM, compared with the two-PFM, can yield SPRs that are closer to the theoretical values and is less affected by noise.

Data traffic compression in spectral photon-counting CT imaging based on human visual characteristics

Spectral computed tomography (CT) with photon-counting detectors (PCDs) can provide a variety of cross-sectional images, showing improved diagnostic capability at low radiation doses. PCDs acquire and divide signals of each energy intensity into separate energy bins and improve the count rate by pixel size miniaturization, which can simultaneously increase spatial resolution. Nevertheless, PCDs do show some limitations in data processing. Acquisition of large-spectrum data requires large spaces of an analog-to-digital converter (ADC) and a memory in each pixel, and this process generates massive amounts of data traffic. The conventional compression techniques used in CT imaging are not suitable for such traffic because they are applied to the CT image data, not the projection data stored by PCDs. This study aimed to secure ADC and memory space and compress the data traffic while maintaining high image resolution by using a number of energy bin's information for computing. This approach was based on a composite method using CT images from high spatial resolution non-spectral CT and low spatial resolution spectral CT. The resolution in non-spectral CT was recognized by assigning grayscale values, while the resolution for spectral CT was maintained with a pseudocolor scale based on visual characteristics. In this paper, we evaluated the image quality against the compression rate to verify our concept.

Low-light phase imaging using in-line digital holography and the transport of intensity equation

In one of our recent studies, we have shown that a large defocusing distance in the transport of intensity equation (TIE) is required to retrieve the phase information in low-light conditions (OSA Continuum 3 (2020) 236). It has been found that image misalignment issues come into the picture due to translation of the camera for large distances, which creates artifacts in phase recovery. The issue of misalignment can be overcome if, instead of the object, we use the digital hologram of the object for the required defocused intensities and then apply the TIE. In this paper, we demonstrate low-light phase imaging by combining digital holography with the TIE. We reconstruct the required multiple intensity distributions from the captured in-line digital hologram. To implement the low-level light illumination, a variable neutral density filter has been used while recording the in-line digital hologram. Simulation and experimental results with different objects (United States air-force chart and glue drop) are presented. To simulate the low-light conditions, a Poisson distribution based photon-counting imaging technique has been applied.

Bayesian regularization restoration algorithm for photon counting images

The photon counting image collected under 10− 4 lux environment has a degraded image quality due to background noises and other problems. Bayesian estimation is a classical approach for photon counting image restoration and regularization has also been widely used in image processing. However, the regularization method is not suitable for photon counting images with extremely lack of information, and the recovery effect of Bayesian estimation in images mixed with unknown noise is not ideal. The main contribution of this paper is that on the basis of Bayesian estimation, the regularization method is introduced to solve the problem of restoring photon counting images mixed with unknown noise under 10− 4 lux environment. The original part is that the gamma distribution of the expected value of photon counting is used as its prior condition, and the error function is expressed as the form of the norm to establish the objective function. Through an approximate iterative solution, the optimal estimation of the photon counting expectation is carried out to achieve the optimal restoration of the photon counting image. Experiments demonstrate that the background noise is effectively removed and the image quality is improved after restoring photon counting images. Also, the final result of the proposed method is superior to other comparative methods in multiple evaluation indexes and achieved better effects.

Image Quality Improvements Based on Motion-Based Deblurring for Single-Photon Imaging

Photon counting imaging can be used to capture clearly photon-limited scenes. In photon counting imaging, information on incident photons is obtained as binary frames (bit-plane frames), which are transformed into a multi-bit image in the reconstruction process. In this process, it is necessary to apply a deblurring method to enable the capture of dynamic scenes without motion blur. In this article, a deblurring method for the high-quality bit-plane frame reconstruction of dynamic scenes is proposed. The proposed method involves the deblurring of units of object motion within a scene through the application of motion compensation to pixels sharing the same motions. This method achieves more efficient motion blur suppression than the application of simple deblurring to pixel block or spatial region units. It also applies a novel technique for accurate motion estimation from the bit-plane frame even in photon-limited situations through the statistical evaluation of the temporal variation of photon incidence. In addition to deblurring, our experimental results also revealed that the proposed method can be applied for denoising, which improves the peak signal-to-noise ratio by 1.2 dB. In summary, the proposed method for bit-plane reconstruction achieves high quality imaging even in photon-limited dynamic scenes.

Development of an optical photon-counting imager with a monolithic Geiger Avalanche Photodiode array

Abstract We have developed a sensor system based on an optical photon-counting imager with high timing resolution, aiming for highly time-variable astronomical phenomena. The detector is a monolithic Geiger-mode avalanche photodiode array customized in a Multi-Pixel Photon Counter with a response time on the order of nanoseconds. This paper evaluates the basic performance of the sensor and confirms the gain linearity, uniformity, and low dark count. We demonstrate the system’s ability to detect the period of a flashing light-emitting diode, using a data acquisition system developed to obtain the light curve with a time bin of 100 μs. The Crab pulsar was observed using a 35-cm telescope without cooling, and the equipment detected optical pulses with a period consistent with the data from the radio ephemeris. Although improvements to the system will be necessary for more reliability, the system has been proven to be a promising device for exploring the time-domain optical astronomy.

Correction of range walk error for underwater photon-counting imaging.

Due to the characteristics of photon-counting LIDAR, there exists range walk error (RWE) when the intensity of the signal fluctuates. In this paper, an effective method to rectify underwater RWE was proposed. The method allows the separation of signal detections from noise detections, and based on a prior model, the method can compensate for RWE. An underwater experiment verified its feasibility and results showed RWE of three parts in a plane was reduced from 75mm to 7mm, from 45mm to 3mm and from 5mm to 0mm, respectively, even when the rate of backscatter photons reached 4.8MHz. The proposed correction method is suitable for high precision underwater photon-counting 3D imaging application, especially when the signal intensity varies sharply.

Photon Counting Imaging with Low Noise and a Wide Dynamic Range for Aurora Observations.

The radiation intensity of observed auroras in the far-ultraviolet (FUV) band varies dramatically with location for aerospace applications, requiring a photon counting imaging apparatus with a wide dynamic range. However, combining high spatial resolution imaging with high event rates is technically challenging. We developed an FUV photon counting imaging system for aurora observation. Our system mainly consists of a microchannel plate (MCP) stack readout using a wedge strip anode (WSA) with charge induction and high-speed electronics, such as a charge sensitive amplifier (CSA) and pulse shaper. Moreover, we constructed an anode readout model and a time response model for readout circuits to investigate the counting error in high counting rate applications. This system supports global rates of 500 kilo counts, 0.610 dark counts s−1 cm−2 at an ambient temperature of 300 K and 111 µm spatial resolution at 400 kilo counts s−1 (kcps). We demonstrate an obvious photon count loss at incident intensities close to the counting capacity of the system. To preserve image quality, the response time should be improved and some noise performance may be sacrificed. Finally, we also describe the correlation between counting rate and imaging resolution, which further guides the design of space observation instruments.

Daytime measurements of bioaerosol simulants using a hyperspectral laser-induced fluorescence LIDAR for biosphere research

A new compact home-built hyper-spectral laser-induced fluorescence (LIF) light detection and ranging (LIDAR) system is presented that can detect and identify bioaerosol clouds in an open atmosphere in daylight up to a distance of 3−4 km. The system is based on a 266 nm laser source and a dual-stage micro-channel plate intensified charge-coupled device sensor, which provides a high-resolution fluorescence spectrum with the sensitivity of a single photon counting imaging detection at a 10 Hz repetition rate. Controlled remote sensing experiments on biological simulants in the aerosol-phase within an enclosed chamber (ΔR=1.2 m) were conducted from a short distance of ∼170 m. A meticulous comparison between the remote fluorescence signal detected by the system and the instantaneous concentration and particle size distribution of the bioaerosol inside the chamber detected by an aerodynamic particle sizer yielded a threshold of ∼20 and 137 μgr s m-3 for the spectral identification of tryptophan and ovalbumin, respectively. This showed that the LIDAR can measure environmental airborne biological aerosol remotely in the daytime and can be utilized as a real-time biosphere research tool. Next, the system was tested in open atmospheric field campaigns in the Israeli desert during the day. It successfully detected bioaerosol clouds at up to 2.5 km in strong wind and sunny conditions. These empirical detection and identification results provide robust estimates that a biological cloud can be sensed at a distance of ∼ 4 km.

Spectral photon-counting CT imaging of colorectal peritoneal metastases: initial experience in rats

Computed tomography imaging plays a major role in the preoperative assessment of tumor burden by providing an accurate mapping of the distribution of peritoneal metastases (PM). Spectral Photon Counting Computed Tomography (SPCCT) is an innovative imaging modality that could overcome the current limitations of conventional CT, offering not only better spatial resolution but also better contrast resolution by allowing the discrimination of multiple contrast agents. Based on this capability, we tested the feasibility of SPCCT in the detection of PM at different time of tumor growth in 16 rats inoculated with CC531 cells using dual-contrast injection protocols in two compartments (i.e. intravenous iodine and intraperitoneal gadolinium or the reverse protocol), compared to surgery. For all peritoneal regions and for both protocols, sensitivity was 69%, specificity was 100% and accuracy was 80%, and the correlation with surgical exploration was strong (p = 0.97; p = 0.0001). No significant difference was found in terms of diagnostic performance, quality of peritoneal opacification or diagnostic quality between the 2 injection protocols. We also showed poor vascularization of peritoneal metastases by measuring low concentrations of contrast agent in the largest lesions using SPCCT, which was confirmed by immunohistochemical analyses. In conclusion, SPCCT using dual-contrast agent injection protocols in 2 compartments is a promising imaging modality to assess the extent of PM in a rat model.

Deep-learning-based single-photon-counting compressive imaging via jointly trained subpixel convolution sampling.

The combination of single-pixel-imaging and single-photon-counting technology can achieve ultrahigh-sensitivity photon-counting imaging. However, its applications in high-resolution and real-time scenarios are limited by the long sampling and reconstruction time. Deep-learning-based compressive sensing provides an effective solution due to its ability to achieve fast and high-quality reconstruction. This paper proposes a sampling and reconstruction integrated neural network for single-photon-counting compressive imaging. To effectively remove the blocking artefact, a subpixel convolutional layer is jointly trained with a deep reconstruction network to imitate compressed sampling. By modifying the forward and backward propagation of the network, the first layer is trained into a binary matrix, which can be applied to the imaging system. An improved deep-reconstruction network based on the traditional Inception network is proposed, and the experimental results show that its reconstruction quality is better than existing deep-learning-based compressive sensing reconstruction algorithms.

Design of a combined X-ray fluorescence Computed Tomography (CT) and photon-counting CT table-top imaging system

This paper demonstrates the capability of a table-top x-ray imaging system to simultaneously image a small animal phantom loaded with Gd and Au contrast agents with photon-counting computed tomography (PCCT) and x-ray fluorescence CT (XFCT). Our table-top system consisted of a diagnostic x-ray tube, translation and rotation stages, a 330 μm-pitch cadmium zinc telluride (CZT) photon-counting detector with six energy bins, and two CdTe spectrometers which detected fluorescent x-rays in 0.5 keV bins. The energy bin thresholds on the CZT detector matched the contrast agent K-edge energies, enabling K-edge PCCT. A 3 cm-diameter phantom containing vials of 1% and 5% Gd and Au solutions by weight, including a mixed 1% Gd/Au vial, was scanned with 0.5 mm Cu-filtered 120 kVp x-rays at 2 mA. A pencil beam geometry was used with 33 translation and 30 rotation steps to form XFCT and K-edge PCCT images. A cone beam geometry with 180 rotation steps was used to form higher-resolution K-edge PCCT images. Three mice were each injected post-mortem with 0.2 mL of 5% Gd, Au, or mixed Gd/Au solutions in the upper torso and imaged similarly to the phantom. The lowest detectable concentration based on the Rose criterion for Gd and Au phantom data was 0.75% and 3.0% for XFCT, 0.81% and 0.82% for pencil beam K-edge PCCT, and 0.79% and 1.5% for cone beam K-edge PCCT. However, cone beam K-edge PCCT images have a much higher spatial resolution than the pencil beam images. The mixed 1% Gd/Au signal was diminished in the K-edge PCCT phantom images. Preliminary mouse images of Gd and Au among the imaging techniques were similar in image quality as the phantom images. This is the first demonstration of simultaneously-acquired XFCT and PCCT of both Gd and Au in a phantom on a table-top imaging system. On our system, cone beam PCCT is best for imaging Gd, pencil beam PCCT is best for imaging Au, and pencil beam XFCT is better suited toward resolving mixtures of contrast agents.

Photon-counting 3D integral imaging with less than a single photon per pixel on average using a statistical model of the EM-CCD camera

We investigate photon-counting 3D integral imaging (PCII) with an electron multiplying charged-coupled device (EM-CCD) camera using dedicated statistical models. Using conventional integral imaging reconstruction methods with this camera in photon-counting conditions may result in degraded reconstructed image quality if multiple photons are detected simultaneously in a given pixel. We propose an estimation method derived from the photon detection statistical model of the EM-CCD to address the problems caused by multiple photons detected at the same pixel and provide improved 3D reconstructions. We also present a simplified version of this statistical method that can be used under the correct conditions. The imaging performance of these methods is evaluated on experimental data by the peak signal-to-noise ratio and the structural similarity index measure. The experiments demonstrate that 3D integral imaging substantially outperforms 2D imaging in degraded conditions. Furthermore, we achieve imaging in photon-counting conditions where, on average, less than a single photon per pixel is detected by the camera. To the best of our knowledge, this is the first report of PCII with the EM-CCD camera employing its statistical model in 3D reconstruction of PCII.

Photon-counting, energy-resolving and super-resolution phase contrast X-ray imaging using an integrating detector.

This work demonstrates the use of a scientific-CMOS (sCMOS) energy-integrating detector as a photon-counting detector, thereby eliminating dark current and read-out noise issues, that simultaneously provides both energy resolution and sub-pixel spatial resolution for X-ray imaging. These capabilities are obtained by analyzing visible light photon clouds that result when X-ray photons produce fluorescence from a scintillator in front of the visible light sensor. Using low-fluence monochromatic X-ray projections to avoid overlapping photon clouds, the centroid of individual X-ray photon interactions was identified. This enabled a tripling of the spatial resolution of the detector to 6.71 ± 0.04 µm. By calculating the total charge deposited by this interaction, an energy resolution of 61.2 ± 0.1% at 17 keV was obtained. When combined with propagation-based phase contrast imaging and phase retrieval, a signal-to-noise ratio of up to 15 ± 3 was achieved for an X-ray fluence of less than 3 photons/mm2.

Transport of intensity equation based photon-counting phase imaging

In low light conditions, such as in astronomy and non-invasive bio-imaging applications, the imaging performance is mostly degraded due to noise. In this paper, we demonstrate a transport of intensity equation based technique that uses photon-counting phase imaging. To achieve the phase imaging in a photon starved condition, a method proposed by Paganin et al. [J. Micros. 214, 51 (2004)10.1111/j.0022-2720.2004.01295.x] has been used. The method uses the fact that the magnitude of the wavefront curvature determines the quality of the recovered phase image for a given noise level and defocus distance. The effectiveness of the proposed method has been illustrated through simulations and experimental results using inexpensive partially coherent illumination. The study can find applications in non-invasive phase imaging.

基于盖革APD阵列的光子计数三维成像

基于盖革APD阵列的光子计数三维成像

远紫外光子计数成像探测器的感应电荷读出方法

远紫外光子计数成像探测器的感应电荷读出方法

Three-Dimensional Laser Imaging Based on a Photon-Counting Avalanche Photodiode Array

Photon-counting detector array is very desired for high-resolution laser imaging based on direct time-of-flight measurement. Such systems have potential applications in remote sensing with long distances. We will perform three-dimensional imaging using a large InGaAs Geiger-mode avalanche photodiode array which has single-photon sensitivity. To improve the image quality with only a few photon detections, the photon counting imaging process is analyzed and a regularization method based on pixel spatial correlation is employed for image reconstruction. The performance of the method is compared with that of conventional maximum likelihood estimation on intensity and range image reconstructions of a building about six hundred meters away.

Development of a pixel readout ASIC for CZT detectors for spectral X-ray photon-counting imaging applications

This paper presents the development of a prototype pixel readout ASIC for CZT detectors fabricated in a 180 nm CMOS process. It consists of a 32 × 32 array of pixels in 100 μm pitch and the EOC (end-of column) circuit for control and data readout. Each pixel integrates a charge sensitive preamplifier, a CR-RC shaper, two discriminators, two 12-bit counters and registers, allowing us to acquire and readout images simultaneously. A local 6-bit register has also been integrated for each pixel for calibration enable and threshold fine tuning, which can be programmed through a SPI slow control interface. A dedicated chip evaluation system was developed and the initial test results showed that the chip worked well. The power consumption was measured to be 38.9 μW per pixel, which could be adjusted by the master bias unit. The gain of the analog front-end was approximately 77.3 mV/fC and the ENC was less than 100 electrons for different shaping times and the input capacitance of about 100 fF. The results were in good agreement with our design specifications. More detailed design and test results will be discussed in this paper.