Scientific Camera Research Articles

A 3D imaging system for dosimetry in FLASH radiotherapy

This study examines the feasibility of reconstructing the spatial dose distribution delivered by a 9 MeV electron beam within a plastic scintillator block using optical tomography. The system is designed for use in 3D-dosimetry for clinical applications in quality assurance and beam characterization, especially with FLASH-beam sources. The proposed detector reconstructs the 3D dose distribution map employing a monolith with 10 cm side, imaged in four different projections by scientific cameras. The 3D dose distribution simulated with Geant4 was reconstructed using a maximum likelihood expectation maximization algorithm applied to the lateral projection, resulting in a longitudinal image with a standard deviation of 0.2 Gy. Furthermore, a preliminary experimental test has been performed.

Near-infrared in vivo imaging system for dynamic visualization of lung-colonizing bacteria in mouse pneumonia.

Conventional animal models of infectious diseases have traditionally relied upon average assessments involving numerous individuals, meaning they do not directly reflect changes in the pathology of an individual. Moreover, in recent years, ethical concerns have resulted in the demand to reduce the number of animals used in such models. Although in vivo imaging offers an effective approach for longitudinally evaluating the pathogenesis of infectious diseases in individual animals, a standardized method has not yet been established. To our knowledge, this study is the first to develop a highly versatile in vivo pulmonary bacterial quantification system utilizing near-infrared luminescence, plasmid-mediated expression of firefly luciferase in bacteria, and a scientific complementary metal-oxide semiconductor camera. Our research holds promise as a useful tool for assessing the efficacy of therapeutic drugs and pathogenesis of infectious diseases.

Simulation‐Training‐Based Deep Learning Approach to Microscopic Ghost Imaging

Herein, deep learning‐ghost imaging (DLGI) based on a digital micromirror device is realized to avoid the difficulties of a charge‐coupled device (CCD) scientific camera being unable to obtain the sample images in extremely weak illumination conditions and to solve the problem of the inverse relationship between imaging quality and imaging time in practical applications. Deep learning for computational ghost imaging typically requires the collection of a large set of labeled experimental data to train a neural network. Herein, we demonstrate that a practically usable neural network can be prepared based on the simulation results. The acquisition results of the CCD scientific camera and the simulation results with low sampling are used as the training set (1000 observations) and we can complete the data acquisition process within one hour. The results show that the proposed DLGI method can be used to significantly improve the quality of the reconstructed images when the sampling rate is 60%. This method also reduces the imaging time and the memory usage, while simultaneously improving the imaging quality. The imaging results of the proposed DLGI method have great significance for application in clinical diagnosis.

SunbYte: an autonomous pointing framework for low-cost robotic solar telescopes on high altitude balloons

The design and usability of a fully autonomous robotic control system (SunbYte - Sheffield University Balloon “lYfted” TElescope) for solar tracking and observational applications onboard high-altitude balloons are addressed here. The design is based on a six-step development plan balancing scientific objectives and practical engineering requirements. The high-altitude solar observational system includes low-cost components such as a Cassegrain-type telescope, stepper motors, harmonic drives, USB cameras and microprocessors. OpenCV installed from ROS (Robotic Operating System), python and C facilitated the collection, compression, and processing of housekeeping and scientific data. This processed data was then transmitted to the ground station through the launch vehicle’s telecommunication link. The SunbYte system allows the brightest spot in the sky, the sun, to be identified, and a telescope pointed towards it with high enough accuracy that a scientific camera can capture images. This paper gathers and presents the results from primarily two missions with the High-Altitude Student Platform (HASP, NASA Balloon Program office and LaSpace). Additionally, a discussion will be made comparing these with an earlier iteration flown with the German-Swedish “REXUS/BEXUS” programme coordinated by the European Space Agency. By capturing and analysing a series of tracking images with the location of the Sun at the calibrated centre, the system demonstrated the tracking capabilities on an unstable balloon during ascent. Housekeeping sensor data was collected to further analyse the thermal and mechanical performance. The low temperature increased friction in the drive train and reduced the responsiveness of the harmonic drive actuation system. This caused some issues which require further work in future missions, for example, with SunbYte 4 and its work when flying with the HEMERA ZPB (Zero Pressure Balloon) program.

Simple and highly accurate measuring method for evaluating the cleanliness levels of laser-cleaned surfaces according to the ISO standard

Surface cleaning is highly demanded in the construction, mechanical, and automotive industries. Laser surface cleaning is increasingly being used due to its advantages such as high selectivity, fast cleaning, and efficient response to many different materials. However, if pulsed lasers with a high peak power are used for surface cleaning, they can damage the surface material if the technological parameters are not controlled appropriately. Therefore, it is necessary to develop accurate and high-speed measurement methods to evaluate the surface quality after cleaning. In this paper, a steel cleaning system using a nano-pulsed laser with a wavelength of 1064 nm was proposed. To evaluate the cleanliness of samples, a simple and rapid measurement system based on image processing was developed. The ISO 8501 standard was chosen as the standard cleanliness level. The surface after cleaning was captured using a scientific camera. The percentage of dark pixels in the captured image was determined using the histogram method. The surface quality after cleaning was determined by comparing it with the cleanliness level of the ISO 8501 standard. Thus, this proposed method is used to evaluate the influence of the average power of the laser source on the cleanliness of the steel surface. This method was observed to be compact, cost-effective, and highly accurate; it also proved to be easy to integrate into cleaning systems.

Pixel-wise programmability enables dynamic high-SNR cameras for high-speed microscopy.

High-speed wide-field fluorescence microscopy has the potential to capture biological processes with exceptional spatiotemporal resolution. However, conventional cameras suffer from low signal-to-noise ratio at high frame rates, limiting their ability to detect faint fluorescent events. Here, we introduce an image sensor where each pixel has individually programmable sampling speed and phase, so that pixels can be arranged to simultaneously sample at high speed with a high signal-to-noise ratio. In high-speed voltage imaging experiments, our image sensor significantly increases the output signal-to-noise ratio compared to a low-noise scientific CMOS camera (~2-3 folds). This signal-to-noise ratio gain enables the detection of weak neuronal action potentials and subthreshold activities missed by the standard scientific CMOS cameras. Our camera with flexible pixel exposure configurations offers versatile sampling strategies to improve signal quality in various experimental conditions.

Development of a new class of temperature-sensitive paints operating in the green spectrum of light for aerodynamic flow applications

Temperature-sensitive paint (TSP) is widely used in aerodynamic measurements, such as detecting laminar to turbulent transition locations, heat transfer measurements, etc. Most conventional TSP luminophores are Ruthenium and Europium complexes, whose peak absorption wavelengths occur at UV or blue spectrum of light. A new class of TSP is developed based on eosin Y as a luminophore. Eosin Y has peak emission and absorption wavelength in the green spectrum, allowing employment of conventional (Nd-YAG) lasers and scientific cameras in aerodynamic applications. The paint achieved a temperature sensitivity of 0.9 % /K, comparable to Rhodamine B based TSP, which operates in the green spectrum. The performance of the TSP is compared with the temperature and its gradient measured using an infrared camera (serving as a reference). The capability of the TSP is tested in three configurations of increasing complexity. The paint successfully detects the laminar to turbulent transition location (third configuration), indicating its promise as an addition to the existing ones for aerodynamic applications.

A dose rate independent 2D Ce-doped YAG scintillating dosimetry system for time resolved beam monitoring in ultra-high dose rate electron “FLASH” radiation therapy

Preclinical studies have shown that radiotherapy treatments benefit from ultra-high dose rate (UHDR) irradiations. These trigger the FLASH-effect, resulting in a strong decrease in normal tissue toxicity with conserved tumor control probability, compared with conventional irradiations. However, the beam parameters to trigger the FLASH-effect and the radiobiological mechanisms behind it remain to be elucidated. A limiting factor in many studies is the lack of accurate real time dosimetry. In this work an innovative solution for 2D real time dosimetry in UHDR electron beams is presented and characterized.The in-house developed ImageDosis system consists of a scientific camera, with high temporal resolution, and a coating, containing 12% of Y3Al5O12:Ce3+ as scintillating material. Reference dosimetry was performed by means of radiochromic film, and a (C38H34P2)MnBr4 point scintillator was used to validate the pulse discrimination properties of the ImageDosis system. Irradiations were performed in two centers (Antwerp and Orsay), with an ElectronFlash accelerator. The ImageDosis system was tested with varying number of pulses, pulse length, pulse repetition frequency (PRF) and energy. In addition, its temporal resolution and 2D properties were investigated.The ImageDosis system showed negligible dose, dose rate and energy dependence for doses up to 13 Gy and average dose rates up to 140 Gy/s, with a dose per pulse up to 2 Gy and a PRF up to 300 Hz. The system is capable of discriminating and measuring the dose of individual pulses and shows promising 2D characteristics that need further optimization.

High-speed and wide-field 3D Raman imaging using flower-like gap-enhanced Raman tags

Raman imaging technology plays a pivotal role in biomedical research, with the pursuit of higher resolution, faster imaging speed, and a larger field of view consistently driving the development of Raman imaging systems. In this work, we propose a high-speed and wide-field three-dimensional (3D) Raman imaging method based on light field microscopy and flower-like gap-enhanced Raman tags (F-GERTs). F-GERTs with enhanced Raman signals and high stability are used to label microbial and cell samples, avoiding the problem of photobleaching. The micro-lens array and scientific camera are incorporated to capture light field Raman images containing spatial information of the sample in a single snapshot acquisition process. The 3D reconstruction algorithm can complete the processing of the light field image within 1 min, reconstructing the 3D Raman image of the sample and the precisely slice structure at different depths. This high-speed and wide-field Raman imaging technology has great potential in the field of real-time 3D Raman imaging of microorganisms and cells.

Hybrid Grid Pattern Star Identification Algorithm Based on Multi-Calibration Star Verification.

In order to solve the star identification problem in the lost space mode for scientific cameras with small fields of view and higher instruction magnitudes, this paper proposes a star identification algorithm based on a hybrid grid pattern. The application of a hybrid pattern generated by multi-calibration stars in the initial matching enables the position distribution features of neighboring stars around the main star to be more comprehensively described and avoids the interference of position noise and magnitude noise as much as possible. Moreover, calibration star filtering is adopted to eliminate incorrect candidates and pick the true matched navigation star from candidate stars in the initial match. Then, the reference star image is utilized to efficiently verify and determine the final identification results of the algorithm via the nearest principle. The performance of the proposed algorithm in simulation experiments shows that, when the position noise is 2 pixels, the identification rate of the algorithm is 96.43%, which is higher than that of the optimized grid algorithm by 2.21% and the grid algorithm by 4.05%; when the magnitude noise is 0.3 mag, the star identification rate of the algorithm is 96.45%, which is superior to the optimized grid algorithm by 2.03% and to the grid algorithm by 3.82%. In addition, in the actual star image test, star magnitude values of ≤12 mag can be successfully identified using the proposed algorithm.

Research on Guide Star Distribution of Sub-Arcsecond Attitude Determination for Microsatellites Reusing Scientific Cameras

Onboard scientific cameras are reused in attitude determination to meet the sub-arcsecond attitude determination accuracy requirements of microsatellites. This approach does not require an additional payload for microsatellites. It involves reusing high-quality optical lenses from the scientific camera and utilizing the peripheral high-quality imaging areas of its square-shaped detector. Separate detectors are placed within these areas as attitude determination detectors to obtain star patterns for closed-loop attitude determination, thereby achieving high-precision attitude determination for microsatellites. The star patterns obtained using this method may pose specific issues due to the relative positions of stars. Through an analysis of the theoretical model that examines the relationship between attitude determination accuracy and the main influencing factors, it is indicated that guide star distribution is one of the main, complex factors determining attitude determination accuracy. A further simulation analysis was conducted on the specific impact of two guide star distribution characteristics—namely, the coverage of guide stars in the attitude determination areas and the proportion of the average field of view occupied by the guide star triangles to the total field of view of the attitude determination areas—on attitude determination accuracy. This study concludes that when the measurement error of the guide stars is bigger than the attitude determination accuracy requirement for its area configuration, four attitude determination areas should be configured. Four attitude determination areas should be prioritized when the measurement error is equal to or smaller than the attitude determination accuracy requirement, followed by the option to configure three attitude determination areas or two symmetric attitude determination areas. When selecting guide stars for star pattern recognition, the guide stars should cover the attitude determination areas as much as possible, and guide stars with a higher proportion of the average field of view occupied by the guide star triangles to the total field of view should be chosen. Finally, experimental validation was conducted using star patterns from dense star fields and sparse star fields. The research results provide an important reference for the optimization of attitude determination area configuration, navigation star catalog construction, and star pattern recognition algorithm research for microsatellites equipped with scientific cameras.

STEM SerialED: achieving high-resolution data for ab initio structure determination of beam-sensitive nanocrystalline materials.

Serial electron diffraction (SerialED), which applies a snapshot data acquisition strategy for each crystal, was introduced to tackle the problem of radiation damage in the structure determination of beam-sensitive materials by three-dimensional electron diffraction (3DED). The snapshot data acquisition in SerialED can be realized using both transmission and scanning transmission electron microscopes (TEM/STEM). However, the current SerialED workflow based on STEM setups requires special external devices and software, which limits broader adoption. Here, we present a simplified experimental implementation of STEM-based SerialED on Thermo Fisher Scientific STEMs using common proprietary software interfaced through Python scripts to automate data collection. Specifically, we utilize TEM Imaging and Analysis (TIA) scripting and TEM scripting to access the STEM functionalities of the microscope, and DigitalMicrograph scripting to control the camera for snapshot data acquisition. Data analysis adapts the existing workflow using the software CrystFEL, which was developed for serial X-ray crystallography. Our workflow for STEM SerialED can be used on any Gatan or Thermo Fisher Scientific camera. We apply this workflow to collect high-resolution STEM SerialED data from two aluminosilicate zeolites, zeolite Y and ZSM-25. We demonstrate, for the first time, ab initio structure determination through direct methods using STEM SerialED data. Zeolite Y is relatively stable under the electron beam, and STEM SerialED data extend to 0.60 Å. We show that the structural model obtained using STEM SerialED data merged from 358 crystals is nearly identical to that using continuous rotation electron diffraction data from one crystal. This demonstrates that accurate structures can be obtained from STEM SerialED. Zeolite ZSM-25 is very beam-sensitive and has a complex structure. We show that STEM SerialED greatly improves the data resolution of ZSM-25, compared with serial rotation electron diffraction (SerialRED), from 1.50 to 0.90 Å. This allows, for the first time, the use of standard phasing methods, such as direct methods, for the ab initio structure determination of ZSM-25.

Development and performance test of a scientific CCD camera prototype for the Earth 2.0 mission

Development and performance test of a scientific CCD camera prototype for the Earth 2.0 mission

Miniaturization and Model-Integration of the Optical Measurement System for Temperature-Sensitive Paint Investigations.

The temperature-sensitive paint (TSP) method, an optical measurement technique, is used for qualitative skin friction visualizations in a wide variety of aerodynamic applications. One such application is the visualization of the laminar-turbulent boundary-layer transition. Optical access to the surface of interest is mandatory for the measurement system, which consists of scientific cameras and LEDs. But the optical access to the area of interest is often impeded by the available windows of the wind tunnel and the wind tunnel model itself, reducing the field of view and the spatial resolution. In some cases, it is of interest to increase the flexibility of the installation of the optical measurement system by reducing its physical dimensions and placing the installation inside the plenum. The DLR Swept flat PlatE Cross-flow TRAnsition (SPECTRA-A) configuration was selected to investigate the influence of two-dimensional steps on the cross-flow-induced boundary layer transition by means of TSP, as part of the EU project Clean Sky 2. The SPECTRA-A configuration consists of two main elements: a flat plate and a displacement body mounted within a very close distance of each other, creating a narrow gap between the two elements. The surface of interest is the area on the flat plate facing the displacement body. The narrow gap limits the utilization of an external camera setup due to poor optical access. A new optical setup consisting of four miniature CMOS machine-vision cameras and five miniature high-power LEDs was integrated into the displacement body. The characteristics of the camera system were analyzed in laboratory tests, establishing that the miniature CMOS machine-vision cameras are suitable for qualitative TSP skin friction visualizations. This was confirmed by successfully measuring the laminar-turbulent boundary-layer transition on the SPECTRA-A configuration. The integrated TSP system is capable of resolving even small variations of the transition location caused by changing the amplitude of the stationary cross-flow instability. The quality of the TSP visualization with the integrated optical system allows for the measurement of the transition location and the wavelength of the stationary cross-flow instability. Overall, a cost-effective TSP visualization system with small space requirements was developed and tested for future applications in wind tunnel models, model support, or side walls of wind tunnels.

Planetary scientific target detection via deep learning: A case study for finding shatter cones in Mars rover images

AbstractPast, present, and forthcoming planetary rover missions to Mars and other planetary bodies are equipped with a large number of scientific cameras. The very large number of images resulting from this, combined with tight time constraints for navigation, measurements, and analyses, pose a major challenge for the mission teams in terms of scientific target evaluation. Shatter cones are the only macroscopic evidence for impact‐induced shock metamorphism and therefore impact craters on Earth. The typical features of shatter cones, such as striations and horsetail structures, are particularly suitable for machine learning methods. The necessary training images do not exist for such a case; therefore, we pursued the approach of producing them artificially. Using PRo3D, a viewer developed for the interactive exploration and geologic analysis of high‐resolution planetary surface reconstructions, we virtually placed shatter cones in 3‐D background scenes processed from true Mars rover imagery. We use PRo3D‐rendered images of such scenes as training data for machine learning architectures. Terrestrial analog studies in Ethiopia supported our lab work and were used to test the resulting neural network of this feasibility study. The result showed that our approach with shatter cones in artificial Mars rover scenes is suitable to train neural networks for automatic detection of shatter cones. In addition, we have identified several aspects that can be used to improve the training of the neural network and increase the recognition rate. For example, using background data with a higher resolution in order to have equal resolution of object (shatter cone) and Martian background and increase the number of objects that can be placed in the training data set. Also using better lighting reconstructions and a better radiometric adaption between object and Martian background would further improve the results.

A single-shot hyperspectral phasor camera for fast, multi-color fluorescence microscopy

Hyperspectral fluorescence imaging improves multiplexed observations of biological samples by utilizing multiple color channels across the spectral range to compensate for spectral overlap between labels. Typically, spectral resolution comes at a cost of decreased detection efficiency, which both hampers imaging speed and increases photo-toxicity to the samples. Here, we present a high-speed, high-efficiency snapshot spectral acquisition method, based on optical compression of the fluorescence spectra via Fourier transform, that overcomes the challenges of discrete spectral sampling: single-shot hyperspectral phasor camera (SHy-Cam). SHy-Cam captures fluorescence spatial and spectral information in a single exposure with a standard scientific CMOS camera, with photon efficiency of over 80%, easily and with acquisition rates exceeding 30 datasets per second, making it a powerful tool for multi-color invivo imaging. Its simple design, using readily available optical components, and its easy integration provide a low-cost solution for multi-color fluorescence imaging with increased efficiency and speed.

Enhanced Chemiluminescence of a Superior Luminol Derivative Provides Sensitive Smartphone‐Based Point‐of‐Care Testing with Enzymatic μPAD

AbstractChemiluminescence (CL) provides ideal conditions for point‐of‐care testing (POCT) with wide dynamic ranges, superior sensitivities, and detection simplicity. It has not arrived routinely in the POCT field due to naturally low quantum yields of typical probes and the lack of sensitive low‐cost detection devices. Here, we developed a universal microfluidic paper‐based analytical device (μPAD) using l‐lactate as model analyte. We demonstrate that a smartphone camera can compete with a scientific CCD camera as performance benchmark when using the strong CL emitter, m‐carboxy luminol, resulting in extraordinary signal‐to‐noise ratios of 67. The μPAD provides CV<10 %, stability at room temperature for≥3 months and simple processing. Furthermore, the μPAD enables the detection of picomoles of the luminophore providing additional design flexibility. Thus, this new CL‐μPAD is available for translating the many CL standard analytical assays performed in microtiter plates, microarrays or other more complex detection strategies to the POC.

Reaching Submillisecond Accuracy in Stellar Occultations and Artificial Satellite Tracking

In recent years, there appeared a need for astronomical observations timed with submillisecond accuracy. These include, e.g., timing stellar occultations by small, subkilometer, or fast near-Earth asteroids and tracking artificial satellites in low-Earth orbit using optical sensors. Precise astrometry of fast-moving satellites and accurate timing of stellar occultations have parallel needs, requiring a reliable time source and good knowledge of camera delays. Thus, there is a need for an external device that would enable equipment and camera testing to check if they reach the required accuracy in time. We designed, constructed, and thoroughly tested a New EXposure Timing Analyser (NEXTA), a Global Navigation Satellite System–based precise timer allowing us to reach an accuracy of 0.1 ms, which is an order of magnitude better than in previously available tools. The device is a simple strip of blinking diodes to be imaged with a camera and compare the imaged time with the internal camera time stamp. Our tests spanned a range of scientific cameras widely used for stellar occultations and ground-based satellite tracking. The results revealed high reliability of both NEXTA and most of the tested cameras but also pointed out that practically all cameras had internal time biases of various levels. NEXTA can serve the community, being easily reproducible with inexpensive components. We provide all the necessary schemes and usage instructions.

Pixelated Micropolarizer Array Based on Carbon Nanotube Films.

A micropolarizer array (MPA) that can be integrated into a scientific camera is proposed as a real-time polarimeter that is capable of extracting the polarization parameters. The MPA is based on highly aligned carbon nanotube (CNT) films inspired by their typical anisotropy and selectivity for light propagation over a wide spectral range. The MPA contains a dual-tier CNT pixel plane with 0° and 45° orientations. The thickness of the dual-tier structure of the CNT-based MPA is limited to less than 2 μm with a pixel size of 7.45 μm × 7.45 μm. The degree of polarization of the CNT-MPA reached 93% at a 632 nm wavelength. The specific designs in structure and semiconductor fabrication procedures are described. Compared with customary MPAs, CNT-based MPA holds great potential in decreasing the cross-talk risk associated with lower film thickness and can be extended to a wide spectral range.

A proton-recoil track imaging system for fast neutrons: the RIPTIDE detector

Fast neutron detection is often based on the neutron-proton elastic scattering reaction: the ionization caused by recoil protons in a hydrogenous material constitutes the basic information for the design and development of a class of neutron detectors. Although experimental techniques have continuously improved, proton-recoil track imaging remains still at the frontier of n-detection systems, due to the high photon sensitivity required. Several state-of-the-art approaches for neutron tracking by using n-p single and double scattering — referred to as Recoil Proton Track Imaging (RPTI) — can be found in the literature. So far, they have showed limits in terms of detection efficiency, complexity, cost, and implementation. In order to address some of these deficiencies, we propose the design of RIPTIDE, a novel recoil-proton track imaging detector in which the light output produced by a fast scintillator is used to perform a complete reconstruction in space and time of the interaction events. The proposed idea is viable thanks to the dramatic advances in low noise and single photon counting achieved in the last decade by new scientific CMOS cameras as well as pixel sensors, like Timepix or MIMOSIS. In this contribution, we report the advances on the RIPTIDE concept: Geant4 Monte Carlo simulations, light collection tests as well as state-of-the-art approach to image readout, processing and fast analysis.