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Minimally invasive endoscopy using coherent fiber bundles shows great potential for numerous applications in biomedical imaging. With a diffuser on the distal side of the fiber bundle and computational image recovery, single-shot 3D imaging is possible by encoding the image volume into 2D speckle patterns. In comparison to equivalent lens systems, a higher space-bandwidth product can be achieved. However, decoding the image with iterative algorithms is time-consuming. Thus, we propose utilizing a neural network for fast 2D and 3D image reconstruction at video rate. In this work, single-shot 3D fluorescence imaging with an ultra-thin endoscope is demonstrated, enabling applications like calcium imaging for in vivo brain diagnostics at cellular resolution.

Lens-based endoscopes offer high lateral resolution, but suffer from rigid imaging properties, such as a fixed focal plane. We present a miniaturized 0.5 mm diameter endoscope in which the objective lens is replaced by an optical diffuser. The intensity information of the object space is scattered and passed to a camera via a coherent fibre bundle. The image is reconstructed by a neural network. The field of view and resolution depend on the object distance. 3D-single-shot imaging up to video rate can be enabled. The approach shows great potential for applications like robust 3D fluorescence imaging.

Optical measurement techniques offer great opportunities in diverse applications, such as lathe monitoring and microfluidics. Doppler-based interferometric techniques enable simultaneous measurement of the lateral velocity and axial distance of a moving object. However, there is a complementarity between the unambiguous axial measurement range and the uncertainty of the distance. Therefore, we present an extended sensor setup, which provides an unambiguous axial measurement range of 1 mm while achieving uncertainties below 100 nm. Measurements at a calibration system are performed. When using a pinhole for emulating a single scattering particle, the tumbling motion of the rotating object is resolved with a distance uncertainty of 50 nm. For measurements at the rough surface, the distance uncertainty amounts to 280 nm due to a lower signal-to-noise ratio. Both experimental results are close to the respective Cramér–Rao bound, which is derived analytically for both surface and single particle measurements. [ABSTRACT FROM AUTHOR]

Significance: Deep learning enables label-free all-optical biopsies and automated tissue classification. Endoscopic systems provide intraoperative diagnostics to deep tissue and speed up treatment without harmful tissue removal. However, conventional multi-core fiber (MCF) endoscopes suffer from low resolution and artifacts, which hinder tumor diagnostics., Aim: We introduce a method to enable unpixelated, high-resolution tumor imaging through a given MCF with a diameter of around 0.65 mm and arbitrary core arrangement and inhomogeneous transmissivity., Approach: Image reconstruction is based on deep learning and the digital twin concept of the single-reference-based simulation with inhomogeneous optical properties of MCF and transfer learning on a small experimental dataset of biological tissue. The reference provided physical information about the MCF during the training processes., Results: For the simulated data, hallucination caused by the MCF inhomogeneity was eliminated, and the averaged peak signal-to-noise ratio and structural similarity were increased from 11.2 dB and 0.20 to 23.4 dB and 0.74, respectively. By transfer learning, the metrics of independent test images experimentally acquired on glioblastoma tissue ex vivo can reach up to 31.6 dB and 0.97 with 14 fps computing speed., Conclusions: With the proposed approach, a single reference image was required in the pre-training stage and laborious acquisition of training data was bypassed. Validation on glioblastoma cryosections with transfer learning on only 50 image pairs showed the capability for high-resolution deep tissue retrieval and high clinical feasibility., (© 2024 The Authors.)

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.

In aircraft engines, thermoacoustic oscillations in the combustion chamber contribute significantly to noise emissions, which, like all other emissions, must be drastically reduced. Thermoacoustic oscillations are not only a concern, they can also be beneficial in hydrogen combustion. This work demonstrates that thermoacoustic density oscillations with amplitudes at least an order of magnitude smaller than those resulting from density gradients in a turbulent flame can be detected using laser interferometric vibrometry. This improvement was made possible by heterodyning a carrier fringe system in background-oriented schlieren (BOS) recordings, which were subsequently analyzed using techniques commonly used for holographic interferometry. In comparison with other BOS evaluation techniques, the filtering of the individual frames in the Fourier domain offers a more efficient computational approach, as it allows for phase averaging of a high number of single recordings to reduce noise from turbulence. To address fringe pattern distortions and cross talk in the Fourier domain, which both have been observed by other authors, we propose background subtraction methods and an optimized background pattern. Additionally, the procedure provides a visualization tool for marking the high turbulence regions of heat release by the variations in fringe amplitude. Finally, the line-of-sight data are reconstructed using the inverse Abel transform, with the data calibrated by laser interferometric techniques, resulting in local values for density oscillations., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s) 2024.)

Multimode fibers hold great promise to advance data rates in optical communications but come with the challenge to compensate for modal crosstalk and mode-dependent losses, resulting in strong distortions. The holographic measurement of the transmission matrix enables not only correcting distortions but also harnessing these effects for creating a confidential data connection between legitimate communication parties, Alice and Bob. The feasibility of this physical-layer-security-based approach is demonstrated experimentally for the first time on a multimode fiber link to which the eavesdropper Eve is physically coupled. Once the proper structured light field is launched at Alice's side, the message can be delivered to Bob, and, simultaneously, the decipherment for an illegitimate wiretapper Eve is destroyed. Within a real communication scenario, we implement wiretap codes and demonstrate confidentiality by quantifying the level of secrecy. Compared to an uncoded data transmission, the amount of securely exchanged data is enhanced by a factor of 538. The complex light transportation phenomena that have long been considered limiting and have restricted the widespread use of multimode fiber are exploited for opening new perspectives on information security in spatial multiplexing communication systems., (Copyright © 2023 Stefan Rothe et al.)

Recent advances in label-free histology promise a new era for real-time diagnosis in neurosurgery. Deep learning using autofluorescence is promising for tumor classification without histochemical staining process. The high image resolution and minimally invasive diagnostics with negligible tissue damage is of great importance. The state of the art is raster scanning endoscopes, but the distal lens optics limits the size. Lensless fiber bundle endoscopy offers both small diameters of a few 100 microns and the suitability as single-use probes, which is beneficial in sterilization. The problem is the inherent honeycomb artifacts of coherent fiber bundles (CFB). For the first time, we demonstrate an end-to-end lensless fiber imaging with exploiting the near-field. The framework includes resolution enhancement and classification networks that use single-shot CFB images to provide both high-resolution imaging and tumor diagnosis. The well-trained resolution enhancement network not only recovers high-resolution features beyond the physical limitations of CFB, but also helps improving tumor recognition rate. Especially for glioblastoma, the resolution enhancement network helps increasing the classification accuracy from 90.8 to 95.6%. The novel technique enables histological real-time imaging with lensless fiber endoscopy and is promising for a quick and minimally invasive intraoperative treatment and cancer diagnosis in neurosurgery., (© 2022. The Author(s).)

The generation of tailored complex light fields with multi-core fiber (MCF) lensless microendoscopes is widely used in biomedicine. However, the computer-generated holograms (CGHs) used for such applications are typically generated by iterative algorithms, which demand high computation effort, limiting advanced applications like fiber-optic cell manipulation. The random and discrete distribution of the fiber cores in an MCF induces strong spatial aliasing to the CGHs, hence, an approach that can rapidly generate tailored CGHs for MCFs is highly demanded. We demonstrate a novel deep neural network-CoreNet, providing accurate tailored CGHs generation for MCFs at a near video rate. The CoreNet is trained by unsupervised learning and speeds up the computation time by two magnitudes with high fidelity light field generation compared to the previously reported CGH algorithms for MCFs. Real-time generated tailored CGHs are on-the-fly loaded to the phase-only spatial light modulator (SLM) for near video-rate complex light fields generation through the MCF microendoscope. This paves the avenue for real-time cell rotation and several further applications that require real-time high-fidelity light delivery in biomedicine., (© 2022. The Author(s).)

Due to their lightweight properties, fiber-reinforced composites are well suited for large and fast rotating structures, such as fan blades in turbomachines. To investigate rotor safety and performance, in situ measurements of the structural dynamic behaviour must be performed during rotating conditions. An approach to measuring spatially resolved vibration responses of a rotating structure with a non-contact, non-rotating sensor is investigated here. The resulting spectra can be assigned to specific locations on the structure and have similar properties to the spectra measured with co-rotating sensors, such as strain gauges. The sampling frequency is increased by performing consecutive measurements with a constant excitation function and varying time delays. The method allows for a paradigm shift to unambiguous identification of natural frequencies and mode shapes with arbitrary rotor shapes and excitation functions without the need for co-rotating sensors. Deflection measurements on a glass fiber-reinforced polymer disk were performed with a diffraction grating-based sensor system at 40 measurement points with an uncertainty below 15 μrad and a commercial triangulation sensor at 200 measurement points at surface speeds up to 300 m/s. A rotation-induced increase of two natural frequencies was measured, and their mode shapes were derived at the corresponding rotational speeds. A strain gauge was used for validation., Competing Interests: The authors declare no conflicts of interest.

Lensless fiber endoscopes are of great importance for keyhole imaging. Coherent fiber bundles (CFB) can be used in endoscopes as remote phased arrays to capture images. One challenge is to image at high speed while correcting aberrations induced by the CFB. We propose the combination of digital optical phase conjugation, using a spatial light modulator, with fast scanning, for which a 2D galvo scanner and an adaptive lens are employed. We achieve the transmission of laser and image scanning through the CFB. Video-rate imaging at 20 Hz in 2D with subcellular resolution is demonstrated in 3D with 1 Hz. The sub-millimeter-diameter scanning endoscope has a great potential in biomedicine, for manipulation, e.g., in optogenetics, as well as in imaging.

Polymer composite rotors offer promising perspectives in high-speed applications such as turbomachinery. However, failure modeling is a challenge due to the material's anisotropy and heterogeneity, which makes high-speed in situ deformation measurements necessary. The challenge is to maintain precision and accuracy in the environment of fast rigid-body movement. A diffraction-grating-based sensor is used for spatio-temporally resolved displacement, tilt, and strain measurements at surface velocities up to 260 m/s with statistical strain uncertainties down to $16\,\,\unicode{x00B5}{\epsilon}$. As a line camera is used, vibrations in the kHz range are measurable in principle. Due to sensor calibration and the use of a novel scan-correlation analysis approach, the rigid-body-movement-induced uncertainties are reduced significantly. The measurement of strain fluctuations on a rotating composite disc show that the crack propagation can be tracked spatially resolved and as a function of the rotational speed, which makes an in situ quantification of the damage state of the rotor possible.

Coherent fiber bundle (CFB)-based endoscopes enable optical keyhole access in applications such as biophotonics. In conjunction with objective lenses, CFBs allow imaging of intensity patterns. In contrast, digital optical phase conjugation enables lensless holographic endoscopes for the generation of pixelation-free arbitrary light patterns. For real-world applications, however, this requires a non-invasive in situ calibration of the complex optical transfer function of the CFB with only single-sided access. We show that after an initial calibration in a forward direction, a differential phase measurement of the back-reflected light allows for tracking and compensating of bending-induced phase distortions. Furthermore, we present a novel in situ calibration procedure based on a programmable guide star, which requires access to only one side of the fiber.

Simultaneous position and velocity measurements enable absolute 3-D shape measurements of fast rotating objects for instance for monitoring the cutting process in a lathe. Laser Doppler distance sensors enable simultaneous position and velocity measurements with a single sensor head by evaluating the scattered light signals. The superposition of several speckles with equal Doppler frequency but random phase on the photo detector results in an increased velocity and shape uncertainty, however. In this paper, we present a novel image evaluation method that overcomes the uncertainty limitations due to the speckle effect. For this purpose, the scattered light is detected with a camera instead of single photo detectors. Thus, the Doppler frequency from each speckle can be evaluated separately and the velocity uncertainty decreases with the square root of the number of camera lines. A reduction of the velocity uncertainty by the order of one magnitude is verified by the numerical simulations and experimental results, respectively. As a result, the measurement uncertainty of the absolute shape is not limited by the speckle effect anymore.

Due to their high stiffness-to-weight ratio, glass fiber-reinforced polymers are an attractive material for rotors, e.g., in the aerospace industry. A fundamental understanding of the material behavior requires non-contact, in-situ dynamic deformation measurements. The high surface speeds and particularly the translucence of the material limit the usability of conventional optical measurement techniques. We demonstrate that the laser Doppler distance sensor provides a powerful and reliable tool for monitoring radial expansion at fast rotating translucent materials. We find that backscattering in material volume does not lead to secondary signals as surface scattering results in degradation of the measurement volume inside the translucent medium. This ensures that the acquired signal contains information of the rotor surface only, as long as the sample surface is rough enough. Dynamic deformation measurements of fast-rotating fiber-reinforced polymer composite rotors with surface speeds of more than 300 m/s underline the potential of the laser Doppler sensor.

The minimum achievable systematic uncertainty of interferometric measurements is fundamentally limited due to speckle noise. Numerical and physical experiments, regarding the achievable measurement uncertainty of Mach-Zehnder based velocity and position sensors, are presented at the example of the laser Doppler distance sensor with phase evaluation. The results show that the measurement uncertainty depends on the number of speckles on the photo detectors. However, while the systematic uncertainty due to the speckle effect decreases, the random uncertainty due to noise from the photo detector increases with increasing speckle number. This results in a minimal total measurement uncertainty for an optimal speckle number on the photo detector, which is achieved by adjusting the aperture of the detection optics.

The precise distance measurement of fast-moving rough surfaces is important in several applications such as lathe monitoring. A nonincremental interferometer based on two mutually tilted interference fringe systems has been realized for this task. The distance is coded in the phase difference between the generated interference signals corresponding to the fringe systems. Large tilting angles between the interference fringe systems are necessary for a high sensitivity. However, due to the speckle effect at rough surfaces, different envelopes and phase jumps of the interference signals occur. At large tilting angles, these signals become dissimilar, resulting in a small correlation coefficient and a high measurement uncertainty. Based on a matching of illumination and receiving optics, the correlation coefficient and the phase difference estimation have been improved significantly. For axial displacement measurements of recurring rough surfaces, laterally moving with velocities of 5 m/s, an uncertainty of 110 nm has been attained. For nonrecurring surfaces, a distance measurement uncertainty of 830 nm has been achieved. Incorporating the additionally measured lateral velocity and the rotational speed, the two-dimensional shape of rotating objects results. Since the measurement uncertainty of the displacement, distance, and shape is nearly independent of the lateral surface velocity, this technique is predestined for fast-rotating objects, such as crankshafts, camshafts, vacuum pump shafts, or turning parts of lathes.

The precise measurement of the distance of fast laterally moving rough surfaces is important in several applications such as lathe monitoring. A nonincremental interferometer based on two tilted interference fringe systems and a precise phase-difference estimation has been realized for this task. However, due to the speckle effect, the two scattered light signals exhibit different phase jumps and random envelopes causing small correlation coefficients and high uncertainties of the phase difference as well as the distance. In this Letter we present for the first time a method to enhance the signal correlation coefficient significantly. The interference signals are generated by scattered light of a rough surface from two different directions. A matching of illumination and receiving optic is performed. By this novel method, distance measurements with an uncertainty down to 1.2 μm at about 10 m/s lateral moving velocity have been achieved. Together with the simultaneously measured lateral velocity, the shape of rotating objects can be precisely determined.