Fiber bundle endocytoscopy

Honeycomb effect elimination in differential phase fiber-bundle-based endoscopy

Fiber-bundle-based endoscopy, with its ultrathin probe and micrometer-level resolution, has become a widely adopted imaging modality for in vivo imaging. However, the fiber bundles introduce a significant honeycomb effect, primarily due to the multi-core structure and crosstalk of adjacent fiber cores, which superposes the honeycomb pattern image on the original image. To tackle this issue, we propose an iterative-free spatial pixel shifting (SPS) algorithm, designed to suppress the honeycomb effect and enhance real-time imaging performance. The process involves the creation of three additional sub-images by shifting the original image by one pixel at 0, 45, and 90 degree angles. These four sub-images are then used to compute differential maps in the x and y directions. By performing spiral integration on these differential maps, we reconstruct a honeycomb-free image with improved details. Our simulations and experimental results, conducted on a self-built fiber bundle-based endoscopy system, demonstrate the effectiveness of the SPS algorithm. SPS significantly improves the image quality of reflective objects and unlabeled transparent scattered objects, laying a solid foundation for biomedical endoscopic applications.

Adaptive noise-resilient deep learning for image reconstruction in multimode fiber scattering

This research offers a comprehensive exploration of three pivotal aspects within the realm of fiber optics and piezoelectric materials. The study delves into the influence of voltage variation on piezoelectric displacement, examines the effects of bending multimode fiber (MMF) on data transmission, and scrutinizes the performance of an autoencoder in MMF image reconstruction with and without additional noise. To assess the impact of voltage variation on piezoelectric displacement, experiments were conducted by applying varying voltages to a piezoelectric material, meticulously measuring its radial displacement. The results revealed a notable increase in displacement with higher voltage, presenting implications for fiber stability and overall performance. Additionally, the investigation into the effects of bending MMF on data transmission highlighted that the bending process causes the fiber to become leaky and radiate power radially, potentially affecting data transmission. This crucial insight emphasizes the necessity for further research to optimize data transmission in practical fiber systems. Furthermore, the performance of an autoencoder model was evaluated using a dataset of MMF images, in diverse scenarios. The autoencoder exhibited impressive accuracy in reconstructing MMF images with high fidelity. The results underscore the significance of ongoing research in these domains, propelling advancements in fiber optic technology.

Near-Infrared Fluorescence Imaging Sensor with Laser Diffuser for Visualizing Photoimmunotherapy Effects under Endoscopy

The drug efficacy evaluation of tumor-selective photosensitive substances was expected to be enabled by imaging the fluorescence intensity in the tumor area. However, fluorescence observation is difficult during treatments that are performed during gastrointestinal endoscopy because of the challenges associated with including the fluorescence filter in the camera part. To address this issue, this study developed a device that integrates a narrow camera and a laser diffuser to enable fluorescence imaging through a forceps port. This device was employed to demonstrate that a laser diffuser with an NIR fluorescence imaging sensor could be delivered through a 3.2 mm diameter port. In addition, fluorescence images of Cetuximab-IR700 were successfully observed in two mice, and the fluorescence intensity confirmed that the fluorescence decayed within 330 s. This device is expected to have practical application as a tool to identify the optimal irradiation dose for tumor-selective photosensitive substances under endoscopy.

Real-timing processing of fiber bundle endomicroscopy images in Python using PyFibreBundle

Fiber imaging bundles allow the transfer of optical images from place-to-place along narrow and flexible conduits. Traditionally used extensively in medical endoscopy, bundles are now finding new applications in endoscopic microscopy and other emerging techniques. PyFibreBundle is an open-source Python package for fast processing of images acquired through imaging bundles. This includes detection and removal of the fiber core pattern by filtering or interpolation, and application of background and flat-field corrections. It also allows images to be stitched together to create mosaics and resolution to be improved by combining multiple shifted images. This paper describes the technical implementation of PyFibreBundle and provides example results from three endomicroscopy imaging systems: color transmission, monochrome transmission, and confocal fluorescence. This allows various processing options to be compared quantitatively and qualitatively, and benchmarking demonstrates that PyFibreBundle can achieve state-of-the-art performance in an open-source package. The paper demonstrates core removal by interpolation and mosaicing at over 100 fps, real-time multi-frame resolution enhancement and the first demonstration of real-time endomicroscopy image processing, including core removal, on a Raspberry Pi single board computer. This demonstrates that PyFibreBundle is potentially a valuable tool for the development of low-cost, high-performance fiber bundle imaging systems.

Large field-of-view short-wave infrared metalens for scanning fiber endoscopy

SIGNIFICANCE

The scanning fiber endoscope (SFE), an ultrasmall optical imaging device with a large field-of-view (FOV) for having a clear forward view into the interior of blood vessels, has great potential in the cardiovascular disease diagnosis and surgery assistance, which is one of the key applications for short-wave infrared biomedical imaging. The state-of-the-art SFE system uses a miniaturized refractive spherical lens doublet for beam projection. A metalens is a promising alternative that can be made much thinner and has fewer off-axis aberrations than its refractive counterpart.

AIM

We demonstrate a transmissive metalens working at 1310 nm for a forward viewing endoscope to achieve a shorter device length and better resolution at large field angles.

APPROACH

We optimize the metalens of the SFE system using Zemax, fabricate it using e-beam lithography, characterize its optical performances, and compare them with the simulations.

RESULTS

The SFE system has a resolution of ∼ 140    μ m at the center of field (imaging distance 15 mm), an FOV of ∼ 70    deg , and a depth-of-focus of ∼ 15    mm , which are comparable with a state-of-the-art refractive lens SFE. The use of the metalens reduces the length of the optical track from 1.2 to 0.86 mm. The resolution of our metalens-based SFE drops by less than a factor of 2 at the edge of the FOV, whereas the refractive lens counterpart has a ∼ 3 times resolution degradation.

CONCLUSIONS

These results show the promise of integrating a metalens into an endoscope for device minimization and optical performance improvement.

Unsupervised full-color cellular image reconstruction through disordered optical fiber

Recent years have witnessed the tremendous development of fusing fiber-optic imaging with supervised deep learning to enable high-quality imaging of hard-to-reach areas. Nevertheless, the supervised deep learning method imposes strict constraints on fiber-optic imaging systems, where the input objects and the fiber outputs have to be collected in pairs. To unleash the full potential of fiber-optic imaging, unsupervised image reconstruction is in demand. Unfortunately, neither optical fiber bundles nor multimode fibers can achieve a point-to-point transmission of the object with a high sampling density, as is a prerequisite for unsupervised image reconstruction. The recently proposed disordered fibers offer a new solution based on the transverse Anderson localization. Here, we demonstrate unsupervised full-color imaging with a cellular resolution through a meter-long disordered fiber in both transmission and reflection modes. The unsupervised image reconstruction consists of two stages. In the first stage, we perform a pixel-wise standardization on the fiber outputs using the statistics of the objects. In the second stage, we recover the fine details of the reconstructions through a generative adversarial network. Unsupervised image reconstruction does not need paired images, enabling a much more flexible calibration under various conditions. Our new solution achieves full-color high-fidelity cell imaging within a working distance of at least 4 mm by only collecting the fiber outputs after an initial calibration. High imaging robustness is also demonstrated when the disordered fiber is bent with a central angle of 60°. Moreover, the cross-domain generality on unseen objects is shown to be enhanced with a diversified object set.

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.

Fourier holographic endoscopy for imaging continuously moving objects

Coherent fiber bundles are widely used for endoscopy, but conventional approaches require distal optics to form an object image and acquire pixelated information owing to the geometry of the fiber cores. Recently, holographic recording of a reflection matrix enables a bare fiber bundle to perform pixelation-free microscopic imaging as well as allows a flexible mode operation, because the random core-to-core phase retardations due to any fiber bending and twisting could be removed in situ from the recorded matrix. Despite its flexibility, the method is not suitable for a moving object because the fiber probe should remain stationary during the matrix recording to avoid the alteration of the phase retardations. Here, we acquire a reflection matrix of a Fourier holographic endoscope equipped with a fiber bundle and explore the effect of fiber bending on the recorded matrix. By removing the motion effect, we develop a method that can resolve the perturbation of the reflection matrix caused by a continuously moving fiber bundle. Thus, we demonstrate high-resolution endoscopic imaging through a fiber bundle, even when the fiber probe changes its shape along with the moving objects. The proposed method can be used for minimally invasive monitoring of behaving animals.

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.

Compressive endoscopic imaging with complementary light modulation

We propose an effective endoscopic imaging method utilizing compressive sensing (CS) theory on the basis of complementary light modulation of a spatial light modulator. Both the simulated and the experimental results show that complementary compressive sensing (CCS) always needs less time to obtain better work than conventional CS with normal modulation at the same sampling rate. First, the speed of CCS is at least twice as fast as CS. Second, in comparison with CS, CCS can improve the signal-to-noise ratio of the reconstructed image by 49.7%, which indicates that this method is of great significance to endoscopic applications in terms of image fidelity and denoising performance.

Binary amplitude-only image reconstruction through a MMF based on an AE-SNN combined deep learning model

The obstacle of imaging through multimode fibers (MMFs) is encountered due to the fact that the inherent mode dispersion and mode coupling lead the output of the MMF to be scattered and bring about image distortions. As a result, only noise-like speckle patterns can be formed on the distal end of the MMF. We propose a deep learning model exploited for computational imaging through an MMF, which contains an autoencoder (AE) for feature extraction and image reconstruction and self-normalizing neural networks (SNNs) sandwiched and employed for high-order feature representation. It was demonstrated both in simulations and in experiments that the proposed AE-SNN combined deep learning model could reconstruct image information from various binary amplitude-only targets going through a 5-meter-long MMF. Simulations indicate that our model works effectively even in the presence of system noise, and the experimental results prove that the method is valid for image reconstruction through the MMF. Enabled by the spatial variability and the self-normalizing properties, our model can be generalized to solve varieties of other computational imaging problems.

Snapshot multispectral endomicroscopy

Multispectral endomicroscopy provides tissue functional information in addition to structural information for accurate disease diagnosis. In this Letter, we propose a snapshot multispectral endomicroscope that employs a fiber bundle to deliver an in-body tissue spatial-spectral datastream to an external compressive spectral imager. Equipped with an end-to-end deep-learning-based reconstruction algorithm, we are able to capture tissue multispectral data in video rates and reconstruct high-resolution multispectral images with up to 24 spectral channels in near-real time.

Video-rate lensless endoscope with self-calibration using wavefront shaping

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.

Establishment of a guided, in vivo, multi-channel, abdominal, tissue imaging approach

Novel tools in humane animal research should benefit the animal as well as the experimentally obtained data. Imaging technologies have proven to be versatile and also in accordance with the demands of the 3 R principle. However, most imaging technologies are either limited by the target organs, number of repetitive imaging sessions, or the maximal resolution. We present a technique-, which enables multicolor abdominal imaging on a tissue level. It is based on a small imaging fiber endoscope, which is guided by a second commercial endoscope. The imaging fiber endoscope allows the distinction of four different fluorescence channels. It has a size of less than 1 mm and can approximately resolve single cells. The imaging fiber was successfully tested on cells in vitro, excised organ tissue, and in mice in vivo. Combined with neural networks for image restauration, high quality images from various abdominal organs of interest were realized. The second endoscope ensured a precise placement of the imaging fiber in vivo. Our approach of guided tissue imaging in vivo, combined with neuronal networks for image restauration, permits the acquisition of fluorescence-microscope like images with minimal invasive surgery in vivo. Therefore, it is possible to extend our approach to repetitive imaging sessions. The cost below 30 thousand euros allows an establishment of this approach in various scenarios.

Image computing for fibre-bundle endomicroscopy: A review

Endomicroscopy is an emerging imaging modality, that facilitates the acquisition of in vivo, in situ optical biopsies, assisting diagnostic and potentially therapeutic interventions. While there is a diverse and constantly expanding range of commercial and experimental optical biopsy platforms available, fibre-bundle endomicroscopy is currently the most widely used platform and is approved for clinical use in a range of clinical indications. Miniaturised, flexible fibre-bundles, guided through the working channel of endoscopes, needles and catheters, enable high-resolution imaging across a variety of organ systems. Yet, the nature of image acquisition though a fibre-bundle gives rise to several inherent characteristics and limitations necessitating novel and effective image pre- and post-processing algorithms, ranging from image formation, enhancement and mosaicing to pathology detection and quantification. This paper introduces the underlying technology and most prevalent clinical applications of fibre-bundle endomicroscopy, and provides a comprehensive, up-to-date, review of relevant image reconstruction, analysis and understanding/inference methodologies. Furthermore, current limitations as well as future challenges and opportunities in fibre-bundle endomicroscopy computing are identified and discussed.

Averaging speckle patterns to improve the robustness of compressive multimode fiber imaging against fiber bend

Fiber bend is a major challenge of multimode fiber (MMF) imaging. More robustness against fiber bend is demonstrated in compressive MMF imaging using mean speckle patterns captured at multiple potential bending configurations beforehand, rather than sticking to single patterns at initial configuration. Experiments demonstrate an overall quality improvement on recovered images than previous work, which is important for robust endoscopic application.

Miniature probe for dual-modality photoacoustic microscopy and white-light microscopy for image guidance: A prototype toward an endoscope

In this study, a novel photoacoustic microscopy (PAM) probe integrating white-light microscopy (WLM) modality that provides guidance for PAM imaging and complementary information is implemented. One single core of an imaging fiber bundle is employed to deliver a pulsed laser for photoacoustic excitation for PAM mode, which provides high resolution with deep penetration. Meanwhile, for WLM mode, the imaging fiber bundle is used to transmit two-dimensional superficial images. Lateral resolution of 7.2 μm for PAM is achieved. Since miniature components are used, the probe diameter is only 1.7 mm. Imaging of phantom and animals in vivo is conducted to show the imaging capability of the probe. The probe has several advantages by introducing the WLM mode, such as being able to conveniently identify regions of interest and align the focus for PAM mode. The prototype of an endoscope shows potential to facilitate clinical photoacoustic endoscopic applications.

Fluorescence-guided stereotactic biopsy: a proof-of-concept study

OBJECTIVE

Accurate histopathological diagnoses are often necessary for treating neuro-oncology patients. However, stereotactic biopsy (STB), a common method for obtaining suspicious tissue from deep or eloquent brain regions, fails to yield diagnostic tissue in some cases. Failure to obtain diagnostic tissue can delay initiation of treatment and may result in further invasive procedures for patients. In this study, the authors sought to determine if the coupling of in vivo optical imaging with an STB system is an effective method for identification of diagnostic tissue at the time of biopsy.

METHODS

A minimally invasive fiber optic imaging system was developed by coupling a 0.65-mm-diameter coherent fiber optic fluorescence microendoscope to an STB system. Human U251 glioma cells were transduced for stable expression of blue fluorescent protein (BFP) to produce U251-BFP cells that were utilized for in vitro and in vivo experiments. In vitro, blue fluorescence was confirmed, and tumor cell delineation by fluorescein sodium (FNa) was quantified with fluorescence microscopy. In vivo, transgenic athymic rats implanted with U251-BFP cells (n = 4) were utilized for experiments. Five weeks postimplantation, the rats received 5–10 mg/kg intravenous FNa and underwent craniotomies overlying the tumor implantation site and contralateral normal brain. A clinical STB needle containing our 0.65-mm imaging fiber was passed through each craniotomy and images were collected. Fluorescence images from regions of interest ipsilateral and contralateral to tumor implantation were obtained and quantified.

RESULTS

Live-cell fluorescence imaging confirmed blue fluorescence from transduced tumor cells and revealed a strong correlation between tumor cells quantified by blue fluorescence and FNa contrast (R2 = 0.91, p < 0.001). Normalized to background, in vivo FNa-mediated fluorescence intensity was significantly greater from tumor regions, verified by blue fluorescence, compared to contralateral brain in all animals (301.7 ± 34.18 relative fluorescence units, p < 0.001). Fluorescence intensity measured from the tumor margin was not significantly greater than that from normal brain (p = 0.89). Biopsies obtained from regions of strong fluorescein contrast were histologically consistent with tumor.

CONCLUSIONS

The authors found that in vivo fluorescence imaging with an STB needle containing a submillimeter-diameter fiber optic fluorescence microendoscope provided direct visualization of neoplastic tissue in an animal brain tumor model prior to biopsy. These results were confirmed in vivo with positive control cells and by post hoc histological assessment. In vivo fluorescence guidance may improve the diagnostic yield of stereotactic biopsies.

Efficient light focusing through an MMF based on two-step phase shifting and parallel phase compensating

Based on a parallel phase compensation scheme, we propose an efficient wavefront shaping method using a spatial light modulator (SLM) for quickly generating a series of focused spots through a multimode fiber (MMF). The compensated phase mask obtained by a two-step phase-shifting technique is loaded to the SLM for generating a focused spot at an arbitrary target position out of the fiber facet. Furthermore, the parallel algorithm we present makes it possible to obtain a series of compensated phase masks, which could be used to generate a series of focused spots at different locations. We experimentally obtained 100 tightly focused spots, with an average focused efficiency of 21.60% and an average focused diameter of 1.9240 μm, and only one-time parallel-compensated phase retrieval is required without multiple iteration optimization.

Robust compressive multimode fiber imaging against bending with enhanced depth of field

Imaging through single multimode fiber prevails its counterpart using single mode fiber bundle on spatial resolution limit and minimum radius. Current multimode fiber imaging suffers from fussy calibration, which can be reduced by recent developed compressive sensing scheme [ [L. V. Amitonova, Opt. Lett. 43, 5427 (2018)]. Experiments demonstrate improvement on depth of field by more than three orders of magnitude, together with robustness against macro fiber bending, which is vital to endoscopic applications.

Fibre-based spectral ratio endomicroscopy for contrast enhancement of bacterial imaging and pulmonary autofluorescence

Fibre-based optical endomicroscopy (OEM) permits high resolution fluorescence microscopy in endoscopically accessible tissues. Fibred OEM has the potential to visualise pathologies targeted with fluorescent imaging probes and provide an in vivo in situ molecular pathology platform to augment disease understanding, diagnosis and stratification. Here we present an inexpensive widefield ratiometric fibred OEM system capable of enhancing the contrast between similar spectra of pathologically relevant fluorescent signals without the burden of complex spectral unmixing. As an exemplar, we demonstrate the potential of the platform to detect fluorescently labelled Gram-negative bacteria in the challenging environment of highly autofluorescent lung tissue in whole ex vivo human lungs.

Optical fiber bundles: Ultra-slim light field imaging probes

Optical fiber bundle microendoscopes are widely used for visualizing hard-to-reach areas of the human body. These ultrathin devices often forgo tunable focusing optics because of size constraints and are therefore limited to two-dimensional (2D) imaging modalities. Ideally, microendoscopes would record 3D information for accurate clinical and biological interpretation, without bulky optomechanical parts. Here, we demonstrate that the optical fiber bundles commonly used in microendoscopy are inherently sensitive to depth information. We use the mode structure within fiber bundle cores to extract the spatio-angular description of captured light rays-the light field-enabling digital refocusing, stereo visualization, and surface and depth mapping of microscopic scenes at the distal fiber tip. Our work opens a route for minimally invasive clinical microendoscopy using standard bare fiber bundle probes. Unlike coherent 3D multimode fiber imaging techniques, our incoherent approach is single shot and resilient to fiber bending, making it attractive for clinical adoption.

Intraoperative Robotic-Assisted Large-Area High-Speed Microscopic Imaging and Intervention

OBJECTIVE

Probe-based confocal endomicroscopy is an emerging high-magnification optical imaging technique that provides in vivo and in situ cellular-level imaging for real-time assessment of tissue pathology. Endomicroscopy could potentially be used for intraoperative surgical guidance, but it is challenging to assess a surgical site using individual microscopic images due to the limited field-of-view and difficulties associated with manually manipulating the probe.

METHODS

In this paper, a novel robotic device for large-area endomicroscopy imaging is proposed, demonstrating a rapid, but highly accurate, scanning mechanism with image-based motion control, which is able to generate histology-like endomicroscopy mosaics. The device also includes, for the first time in robotic-assisted endomicroscopy, the capability to ablate tissue without the need for an additional tool.

RESULTS

The device achieves preprogrammed trajectories with positioning accuracy of less than 30 [Formula: see text], while the image-based approach demonstrated that it can suppress random motion disturbances up to [Formula: see text]. Mosaics are presented from a range of ex vivo human and animal tissues, over areas of more than [Formula: see text], scanned in approximate [Formula: see text].

CONCLUSION

This paper demonstrates the potential of the proposed instrument to generate large-area, high-resolution microscopic images for intraoperative tissue identification and margin assessment.

SIGNIFICANCE

This approach presents an important alternative to current histology techniques, significantly reducing the tissue assessment time, while simultaneously providing the capability to mark and ablate suspicious areas intraoperatively.

Optical resolution photoacoustic microscopy based on multimode fibers

Photoacoustic microscopy (PAM) is a multiscale imaging technique. In optical-resolution photoacoustic microscopy (OR-PAM), a single mode (SM) fiber is normally used as the source of optical excitation to be focused into a diffraction-limited spot. Recent advances in OR-PAM have improved its imaging speed using microelectromechanical systems (MEMS). Here we report for the first time the use of a multimode (MM) fiber as the optical excitation source for high resolution OR-PAM in vivo imaging. A high-speed MEMS scanner based OR-PAM system combined with the mechanical movement to provide wide area imaging was used. The use of multimode fiber for achieving tight optical focus would make the optical alignment easier and high repetition rate light delivery possible for high-speed OR-PAM imaging. A lateral resolution of 3.5 µm and axial resolution of 27 µm with ~1.5 mm imaging depth was successfully demonstrated using the system. The efficacy of multimode fibers for achieving tight focus is beneficial for developing high-resolution photoacoustic endoscopy systems and can be combined with other optical endoscopic imaging modalities as well.

Fiber bundle endomicroscopy with multi-illumination for three-dimensional reflectance image reconstruction

Bundled fiber optics allow in vivo imaging at deep sites in a body. The intrinsic optical contrast detects detailed structures in blood vessels and organs. We developed a bundled-fiber-coupled endomicroscope, enabling stereoscopic three-dimensional (3-D) reflectance imaging with a multipositional illumination scheme. Two illumination sites were attached to obtain reflectance images with left and right illumination. Depth was estimated by the horizontal disparity between the two images under alternative illuminations and was calibrated by the targets with known depths. This depth reconstruction was applied to an animal model to obtain the 3-D structure of blood vessels of the cerebral cortex (Cereb cortex) and preputial gland (Pre gla). The 3-D endomicroscope could be instrumental to microlevel reflectance imaging, improving the precision in subjective depth perception, spatial orientation, and identification of anatomical structures.

Endomicroscopy for Computer and Robot Assisted Intervention

Endomicroscopy is a new technique that allows human tissue to be characterized in vivo and in situ, circumventing the need for conventional biopsy and histology. Despite increased application and growing research interests in this area, the clinical application of endomicroscopy, however, is limited by difficulties in ergonomic control, consistent probe-tissue contact, large area surveillance, and retargeting. Recently, advances in high-speed imaging, mosaicing, and robotics have aimed to address these difficulties. The development of robot-assisted devices in particular has shown great promises in extending the clinical potential of endomicroscopy. Issues related to miniaturization, adaptation to tissue deformation, control stability, force and position compensation, cost, and sterility are being pursued by both research and commercial communities. In this review, recent clinical and technical developments in different aspects of computer and robotic assisted endomicroscopy interventions including instrumentation, multiscale integration, and high-speed imaging techniques are presented. We further address emerging trends and new research opportunities toward more widespread clinical acceptance of robotically assisted endomicroscopy technologies.

In vivo bioluminescence and reflectance imaging of multiple organs in bioluminescence reporter mice by bundled-fiber-coupled microscopy

Bioluminescence imaging (BLI) is used in biomedical research to monitor biological processes within living organisms. Recently, fiber bundles with high transmittance and density have been developed to detect low light with high resolution. Therefore, we have developed a bundled-fiber-coupled microscope with a highly sensitive cooled-CCD camera that enables the BLI of organs within the mouse body. This is the first report of in vivo BLI of the brain and multiple organs in luciferase-reporter mice using bundled-fiber optics. With reflectance imaging, the structures of blood vessels and organs can be seen clearly with light illumination, and it allowed identification of the structural details of bioluminescence images. This technique can also be applied to clinical diagnostics in a low invasive manner.

Five-lens, easy-to-implement miniature objective for a fluorescence confocal microendoscope

A fluorescence confocal microendoscope requires a high-performance miniature objective. We present a miniature objective comprising four glass lenses and one plastic aspheric lens. The 0.5 NA objective is achromatized in the wavelength range of 488-550 nm, has a field of view (FOV) of 360 μm, and an outer diameter of 2.6 mm. The assembled miniature objective can resolve features separated by as little as 0.78 μm. The imaging quality of the fluorescence confocal microendoscope with the miniature objective is similar to that of a commercial confocal microscope. It can resolve cellular structures such as crypt structures and epithelial cells.

Color reflectance fiber bundle endomicroscopy without back-reflections

Coherent fiber imaging bundles can be used as passive probes for reflectance-mode endomicroscopy providing that the back-reflections from the fiber ends are efficiently rejected. We describe an approach specific to widefield endomicroscopy in which light is injected into a leached fiber bundle near the distal end, thereby avoiding reflections from the proximal face. We use this method to demonstrate the color widefield reflectance endomicroscopy of ex vivo animal tissue.