Imaging Fiber Bundle Research Articles

Divertor tungsten source monitoring by A visible spectroscopy diagnostic on EAST

EAST has been upgraded with top and bottom tungsten divertors to facilitate the high power long pulse operation. A visible spectroscopy diagnostic has been developed progressively to monitor W source as well as line emissions from other particles (e.g., D, He, Li, B, C, N, O, Ne, Ar, Mo, D2, WD) in the divertors. Two sets of lens installed in mid-plane port view tangentially the top and bottom divertors, respectively. Two types of optical fibers transfer the plasma light collected by the lens to three different detecting modules. High spectral resolution (λ/Δλ ∼ 14000) can be achieved by the detecting module consisting of spectrometer and Electron-Multiplying Charge Coupled Device (EMCCD), high temporal resolution (50 μs) is obtained by filtered photoelectric multiplier (PMT), and high spatial resolution (1 mm) is acquired by Complementary Metal-Oxide-Semiconductor Transistor (CMOS) camera with collimation optics. The multichannel optical fiber array with 500 μm core diameter is used to connect the lens and the first two detecting modules. The imaging fiber bundle with 30 μm core diameter transmits the two-dimensional divertor plasma light to the third detecting module, i.e. collimation optics and CMOS camera. The diagnostic is operated automatically in normal EAST discharges to support experimental operation and divertor physics study. The paper presents a technical description of the diagnostic and typical measurements during EAST discharges.

Design of a new scintillator-based fast ion loss detector on the HL-2A tokamak

A new scintillator-based fast ion loss detector (FILD) has been devised for the HL-2A tokamak, with the objective of discerning the temporal evolution of energy and pitch angle among lost fast ions. A code named FILD Simulation (FSC) has been developed to assist in the design of the detector head and the interpretation of experimental data. By optimising the geometric design, the resolutions of energy and pitch angle are optimised to 5 keV and 3°, respectively. A branched imaging fiber bundle is used to relay the fluorescence image on the scintillator to two distinct instruments. One of these is a high-speed camera, while the other is a silicon photomultiplier tube (SiPM) array with a sampling rate of up to 1 MSamples/s. This configuration enables the attainment of superior temporal and spatial resolution, as well as high photon sensitivity.

DTI Tractography

The DTI technology used to observe the Nerve fascicle - Nerve fascicle imaging was also discussed in detail. Two types of deterministic and probabilistic traction imaging were compared from effectiveness and computational efficiency perspectives. Then an experimental study was conducted using different software to compare the fiber bundles of the subjects brain and the normal brain and to evaluate the impact of different angle thresholds on the number of observable fiber bundles. Research has confirmed that the subjects whole brain fiber bundle imaging reconstruction was successful, and there was no significant difference compared to the normal brain fiber bundle. The study also found a specific quantitative relationship between the angle threshold and the number of fiber bundles. This experiment also explored the differences in connectivity strength between the brain regions of the left and right brains and their significance.

2D3C Measurement Of Velocity, Pressure And Temperature Fields In A Intake Flow Of An Air Turbine By Filtered Rayleigh Sattering (FRS) And Validation With LDV And PIV

A Filtered Rayleigh Scattering Technique is implemented in two different experimental setups and compared to the established velocity measurement techniques Laser Doppler Anemometry (LDA) and Particle Image Velocimetry (PIV). The Frequency Scanning Filtered Rayleigh Scattering Method employed uses an imagefiber bundle which allows for the simultaneous observation of the flow situation from six independent perspectives, utilizing only one sCMOS camera. A testrig with a nominal diameter of 80 mm was implemented by ILA R&D GmbH. Here measurements with straight pipe flow and a swirl generator were realised, as well as comparisions with LDA. A second experiment utilized Cranfields University’s Complex Intake Facility (CCITF), enabling the simulation of the flow field for an engine intake as observed behind an S-Duct diffuser. The diameter in the measuring plane was 160 mm. Measurements up to a mach number of 0.4 were performed and compared with HighSpeed Stereo-PIV (S-PIV) measurements. Good agreement was achieved in respect to both the absolute magnitude of the velocity measurements as well as to the resolution of complex flow structures. The developed FRS multi-view Setup is able to simultaneously determine the 3D velocity components, the pressure and the temperature on a measurement plane with high resolution and without seeding. After calibration the FRS system yields the pressure and temperature within 3 percent respectively 0.8 percent of the reference values. The measured velocity was within 1-2 m/s of the reference.

Development Of An Endoscopic, Absorption Corrected And Calibrated OH Laser Induced Fluorescence Probe System for High Pressure Combustion Diagnostics

We present the design and preliminary results of an endoscopic OH laser-induced fluorescence (LIF) system that is capable of acquiring 1D-line measurements in high pressure combustion processes within large-scale test facilities. The system can be exploited to acquire line-of-sight OH-chemiluminescence images and absorption corrected absolute OH-species concentration from which additionally temperature distribution can be extracted in case of lean mixtures in chemical equilibrium. Different critical components, such as light guides for high power UV laser pulses and flexible UV image guides, were first tested and characterized in a laboratory setup. Optimization regarding pulse energy and beam quality led to the selection of an 1m long hollow core fiber for laser light delivery as a central element for the experimental setup despite high losses caused by bending the fiber. The image transfer is accomplished by a 7m long flexible UV image bundle, which is preferred to the use of a rigid borescope in harsh environments. We designed the endoscopic UV optics using readily available parts and achieved an approximated image resolution of 21.6 line pairs/mm. Additionally, post-processing methods, such as flat-field correction, can improve the image quality substantially and remove the pixilation effect of the fiber bundle structure nearly completely. To validate the complete system, probe-based qualitative OH-LIF measurements were performed in a well-known laminar flame of a matrix burner, which serves as a mock-up for anticipated applications in an industrial test environment with a technology readiness level (TRL) greater than 4. The final step consists of the integration of the miniaturized optics into a cooled probe system which protects the sensitive optics against the harsh environment of an aero-engine sector combustor. For this purpose, two probe systems were designed to include, on the one hand, the endoscope optics together with the fiber image bundle end tip and, on the other hand, the laser emitting and receiving system for performing an absorption measurement needed to quantify the recorded LIF signal.

Two-wavelength holographic micro-endoscopy

In this paper, we present a method for micro-endoscopic topography measurement utilizing two-wavelength holography. Initially, we evaluate the inter-core dispersion and cross-talk of two commercially available imaging fiber bundles (CFBs) and introduce the concept of virtual surface roughness as a limiting factor of achievable measurement resolution. Subsequently, we describe a micro-endoscope setup incorporating 3D-printed micro-optics, resulting in a total diameter of less than 450 µm. We evaluate the measurement accuracy using a pyramid-shaped test object and demonstrate that a relative measurement error of 7.5% can be achieved with a simple phase unwrapping approach. Moreover, we demonstrate how leveraging a deep learning approach from existing literature, tailored for heavily noisy phase maps, effectively reduces the relative measurement error. The standard deviation of the measurement error is 4.2 times lower with the deep learning approach.

Single-Shot Standoff Hyperspectral Raman Imaging of a Chemical Warfare Agent Simulant.

We demonstrate single-shot standoff hyperspectral Raman imaging of liquid diisopropyl methylphosphonate at a standoff distance of 1 m using two different techniques: multi-bandpass filter imaging (MBFI) and fiber-bundle imaging spectroscopy (FBIS). We find that MBFI has good spatial resolution, but poor spectral resolution, due to the limitations of commercially available bandpass filters. On the other hand, we find FBIS to have excellent spectral resolution, but limited spatial resolution due to the relatively small number of fibers in a bundle. For FBIS, we also determine, for a 1 m standoff distance, a minimum pump fluence of 10 mJ/cm to obtain good single-shot spectra.

Robust autofocus method based on patterned active illumination and image cross-correlation analysis.

For the effectiveness of a computer-aided diagnosis system, the quality of whole-slide image (WSI) is the foundation, and a useful autofocus method is an important part of ensuring the quality of WSI. The existing autofocus methods need to balance focusing speed and focusing accuracy, and need to be optimized separately for different samples or scenes. In this paper, a robust autofocus method based on fiber bundle illumination and image normalization analysis is proposed. For various application scenes, it meets the requirements of autofocusing through active illumination, such as bright field imaging and fluorescence imaging. For different structures on samples, it ensures the autofocusing accuracy through image analysis. The experimental results imply that the autofocusing method in this paper can effectively track the change of the distance from the sample to the focal plane and significantly improve the WSI quality.

Improved resolution in fiber bundle inline holographic microscopy using multiple illumination sources.

Recent work has shown that high-quality inline holographic microscopy images can be captured through fiber imaging bundles. Speckle patterns arising from modal interference within the bundle cores can be minimized by use of a partially-coherent optical source such as an LED delivered via a multimode fiber. This allows numerical refocusing of holograms from samples at working distances of up to approximately 1 mm from the fiber bundle before the finite coherence begins to degrade the lateral resolution. However, at short working distances the lateral resolution is limited not by coherence, but by sampling effects due to core-to-core spacing in the bundle. In this article we demonstrate that multiple shifted holograms can be combined to improve the resolution by a factor of two. The shifted holograms can be rapidly acquired by sequentially firing LEDs, which are each coupled to their own, mutually offset, illumination fiber. Following a one-time calibration, resolution-enhanced images are created in real-time at an equivalent net frame rate of up to 7.5 Hz. The resolution improvement is demonstrated quantitatively using a resolution target and qualitatively using mounted biological slides. At longer working distances, beyond 0.6 mm, the improvement is reduced as resolution becomes limited by the source spatial and temporal coherence.

Photonic neural probe enabled microendoscopes for light-sheet light-field computational fluorescence brain imaging.

Light-sheet fluorescence microscopy is widely used for high-speed, high-contrast, volumetric imaging. Application of this technique to in vivo brain imaging in non-transparent organisms has been limited by the geometric constraints of conventional light-sheet microscopes, which require orthogonal fluorescence excitation and collection objectives. We have recently demonstrated implantable photonic neural probes that emit addressable light sheets at depth in brain tissue, miniaturizing the excitation optics. Here, we propose a microendoscope consisting of a light-sheet neural probe packaged together with miniaturized fluorescence collection optics based on an image fiber bundle for lensless, light-field, computational fluorescence imaging. Foundry-fabricated, silicon-based, light-sheet neural probes can be packaged together with commercially available image fiber bundles to form microendoscopes for light-sheet light-field fluorescence imaging at depth in brain tissue. Prototype microendoscopes were developed using light-sheet neural probes with five addressable sheets and image fiber bundles. Fluorescence imaging with the microendoscopes was tested with fluorescent beads suspended in agarose and fixed mouse brain tissue. Volumetric light-sheet light-field fluorescence imaging was demonstrated using the microendoscopes. Increased imaging depth and enhanced reconstruction accuracy were observed relative to epi-illumination light-field imaging using only a fiber bundle. Our work offers a solution toward volumetric fluorescence imaging of brain tissue with a compact size and high contrast. The proof-of-concept demonstrations herein illustrate the operating principles and methods of the imaging approach, providing a foundation for future investigations of photonic neural probe enabled microendoscopes for deep-brain fluorescence imaging in vivo.

Development of fully fiber-coupled phosphor thermometry imaging for combustion applications

Fully fiber-coupled phosphor thermometry imaging was demonstrated in an atmospheric fuel-flexible jet-stabilized combustor operated with methane–hydrogen–air flames. Different fuel-air mixedness and operating conditions ranging from 100% methane to 100% hydrogen were investigated. The phosphor GdAlO3:Cr was excited at 532 nm using a fiber bundle, while an imaging fiber bundle was used for signal detection. The presented setup allowed to cover a temperature range from 400–1100 °C with a precision of 0.2–2%. Temperature maps of the combustor walls for six operating conditions will be presented and the influence of the different flame conditions on the wall temperatures will be discussed.

Feature-enhanced fiber bundle imaging based on light field acquisition

Feature-enhanced fiber bundle imaging based on light field acquisition

Correction procedure for a tomographic optical setup employing imaging fiber bundles andintensified cameras.

For reliable tomographic measurements the underlying 2D images from different viewing angles must be matched in terms of signal detection characteristics. Non-linearity effects introduced by intensified cameras and spatial intensity variations induced from inhomogeneous transmission of the optical setup can lead, if not corrected, to a biased tomographic reconstruction result. This paper presents a complete correction procedure consisting of a combination of a non-linearity and flatfield correction for a tomographic optical setup employing imaging fiber bundles and four intensified cameras. Influencing parameters on the camera non-linearity are investigated and discussed. The correction procedure is applied to 3D temperature measurements by two-color pyrometry and compared to results without correction. The present paper may serve as a guideline for an appropriate correction procedure for any type of measurement involving optical tomography and intensified cameras.

Fast bidirectional vector wave propagation method showcased on targeted noise reduction in imaging fiber bundles using 3D-printed micro optics.

In order to extend simulation capabilities for reflective and catadioptric 3D-printed micro optics, we present a fast bidirectional vector wave propagation method (BWPM). Contrary to established fast simulation methods like the wave propagation method (WPM), the BWPM allows for the additional consideration of reflected and backwards propagating electric fields. We study the convergence of the BWPM and investigate relevant simulation examples. Especially, the BWPM is used for evaluation of 3D-printed index matching caps (IMCs) in order to suppress back reflected light in imaging fibers, used for keyhole access endoscopy. Simulations studying the viability of IMCs are followed up with experimental investigations. We demonstrate that 3D-printed IMCs can be used to suppress noise caused by back reflected light, that otherwise would prohibit the use of imaging fibers in an epi-illumination configuration.

Iterative prototyping based on lessons learned from the falloposcope in vivo pilot study experience.

High grade serous ovarian cancer is the most deadly gynecological cancer, and it is now believed that most cases originate in the fallopian tubes (FTs). Early detection of ovarian cancer could double the 5-year survival rate compared with late-stage diagnosis. Autofluorescence imaging can detect serous-origin precancerous and cancerous lesions in ex vivo FT and ovaries with good sensitivity and specificity. Multispectral fluorescence imaging (MFI) can differentiate healthy, benign, and malignant ovarian and FT tissues. Optical coherence tomography (OCT) reveals subsurface microstructural information and can distinguish normal and cancerous structure in ovaries and FTs. We developed an FT endoscope, the falloposcope, as a method for detecting ovarian cancer with MFI and OCT. The falloposcope clinical prototype was tested in a pilot study with 12 volunteers to date to evaluate the safety and feasibility of FT imaging prior to standard of care salpingectomy in normal-risk volunteers. In this manuscript, we describe the multiple modifications made to the falloposcope to enhance robustness, usability, and image quality based on lessons learned in the clinical setting. The diameter falloposcope was introduced via a minimally invasive approach through a commercially available hysteroscope and introducing a catheter. A navigation video, MFI, and OCT of human FTs were obtained. Feedback from stakeholders on image quality and procedural difficulty was obtained. The falloposcope successfully obtained images in vivo. Considerable feedback was obtained, motivating iterative improvements, including accommodating the operating room environment, modifying the hysteroscope accessories, decreasing endoscope fragility and fiber breaks, optimizing software, improving fiber bundle images, decreasing gradient-index lens stray light, optimizing the proximal imaging system, and improving the illumination. The initial clinical prototype falloposcope was able to image the FTs, and iterative prototyping has increased its robustness, functionality, and ease of use for future trials.

Infrared fiber bundle image super-resolved based on computational imaging

As the representative of flexibility in optical imaging media, in recent years, fiber bundles have emerged as a promising architecture in the development of compact visual systems. Dedicated to tackling the problems of universal honeycomb artifacts and low signal-to-noise ratio (SNR) imaging in fiber bundles, the iterative super-resolution reconstruction network based on a physical model is proposed. Under the constraint of solving the two subproblems of data fidelity and prior regular term alternately, the network can efficiently “regenerate” the lost spatial resolution with deep learning. By building and calibrating a dual-path imaging system, the real-world dataset where paired low resolution (LR) - high resolution (HR) images on the same scene can be obtained simultaneously. Numerical results on both USAF target and complex target objects demonstrate that the algorithm can restore high contrast images without pixilated noise. On the basis of super-resolution reconstruction, compound eye image composition based on fiber bundle is also realized in this paper for the actual imaging requirements. The proposed work is the first to apply a physical model-based network structure to fiber bundle imaging in the long-wave infrared band, effectively promoting the engineering application of thermal radiation detection.

Block-based compressed sensing for fast optic fiber bundle imaging with high spatial resolution.

The resolution of traditional fiber bundle imaging is usually limited by the density and the diameter of the fiber cores. To improve the resolution, compression sensing was introduced to resolve multiple pixels from a single fiber core, but current methods have the drawbacks of excessive sampling and long reconstruction time. In this paper, we present, what we believe to be, a novel block-based compressed sensing scheme for fast realization of high-resolution optic fiber bundle imaging. In this method, the target image is segmented into multiple small blocks, each of which covers the projection area of one fiber core. All block images are independently and simultaneously sampled and the intensities are recorded by a two-dimensional detector after they are collected and transmitted through corresponding fiber cores. Because the size of sampling patterns and the sampling numbers are greatly reduced, the reconstruction complexity and reconstruction time are also decreased. According to the simulation analysis, our method is 23 times faster than the current compressed sensing optical fiber imaging for reconstructing a fiber image of 128 × 128 pixels, while the sampling number is only 0.39%. Experiment results demonstrate that the method is also effective for reconstructing large target images and the number of sampling does not increase with the size of the image. Our finding may provide a new idea for high-resolution real-time imaging of fiber bundle endoscope.

Novel Design and Application of High-NA Fiber Imaging Bundles for In Vivo Brain Imaging with Two-Photon Scanning Fluorescence Microscopy.

Here, we provide experimental verification supporting the use of short-section imaging bundles for two-photon microscopy imaging of the mouse brain. The 8 mm long bundle is made of a pair of heavy-metal oxide glasses with a refractive index contrast of 0.38 to ensure a high numerical aperture NA = 1.15. The bundle is composed of 825 multimode cores, ordered in a hexagonal lattice with a pixel size of 14 μm and a total diameter of 914 μm. We demonstrate successful imaging through custom-made bundles with 14 μm resolution. As the input, we used a 910 nm Ti-sapphire laser with 140 fs pulse and a peak power of 9 × 104 W. The excitation beam and fluorescent image were transferred through the fiber imaging bundle. As test samples, we used 1 μm green fluorescent latex beads, ex vivo hippocampal neurons expressing green fluorescent protein and cortical neurons in vivo expressing the fluorescent reporter GCaMP6s or immediate early gene Fos fluorescent reporter. This system can be used for minimal-invasive in vivo imaging of the cerebral cortex, hippocampus, or deep brain areas as a part of a tabletop system or an implantable setup. It is a low-cost solution, easy to integrate and operate for high-throughput experiments.

Fiber Bundle Image Reconstruction Using Convolutional Neural Networks and Bundle Rotation in Endomicroscopy.

Fiber-bundle endomicroscopy has several recognized drawbacks, the most prominent being the honeycomb effect. We developed a multi-frame super-resolution algorithm exploiting bundle rotation to extract features and reconstruct underlying tissue. Simulated data was used with rotated fiber-bundle masks to create multi-frame stacks to train the model. Super-resolved images are numerically analyzed, which demonstrates that the algorithm can restore images with high quality. The mean structural similarity index measurement (SSIM) improved by a factor of 1.97 compared with linear interpolation. The model was trained using images taken from a single prostate slide, 1343 images were used for training, 336 for validation, and 420 for testing. The model had no prior information about the test images, adding to the robustness of the system. Image reconstruction was completed in 0.03 s for 256 × 256 images indicating future real-time performance is within reach. The combination of fiber bundle rotation and multi-frame image enhancement through machine learning has not been utilized before in an experimental setting but could provide a much-needed improvement to image resolution in practice.

Computational imaging with spectral coding increases the spatial resolution of fiber optic bundles.

Fiber optic bundles are used in narrow-diameter medical and industrial instruments for acquiring images from confined locations. Images transmitted through these bundles contain only one pixel of information per fiber core and fail to capture information from the cladding region between cores. Both factors limit the spatial resolution attainable with fiber bundles. We show here that computational imaging (CI) can be combined with spectral coding to overcome these two fundamental limitations and improve spatial resolution in fiber bundle imaging. By acquiring multiple images of a scene with a high-resolution mask pattern imposed, up to 17 pixels of information can be recovered from each fiber core. A dispersive element at the distal end of the bundle imparts a wavelength-dependent lateral shift on light from the object. This enables light that would otherwise be lost at the inter-fiber cladding to be transmitted through adjacent fiber cores. We experimentally demonstrate this approach using synthetic and real objects. Using CI with spectral coding, object features 5× smaller than individual fiber cores were resolved, whereas conventional imaging could only resolve features at least 1.5× larger than each core. In summary, CI combined with spectral coding provides an approach for overcoming the two fundamental limitations of fiber optic bundle imaging.