Lenslet array tunable snapshot imaging spectrometer (LATIS) for hyperspectral fluorescence microscopy

Development of a large volume line scanning, high spectral range and resolution 3D hyperspectral photoluminescence imaging microscope for diamond and other high refractive index materials

Hyperspectral photoluminescence (PL) imaging is a powerful technique that can be used to understand the spatial distribution of emitting species in many materials. Volumetric hyperspectral imaging of weakly emitting color centers often necessitates considerable data collection times when using commercial systems. We report the development of a line-scanning hyperspectral imaging microscope capable of measuring the luminescence emission spectra for diamond volumes up to 2.20 × 30.00 × 6.30 mm with a high lateral spatial resolution of 1-3 µm. In an single X-λ measurement, spectra covering a 711 nm range, in a band from 400-1100 nm, with a spectral resolution up to 0.25 nm can be acquired. Data sets can be acquired with 723 (X) × 643 (Y) × 1172 (λ) pixels at a rate of 6 minutes/planar image slice, allowing for volumetric hyperspectral imaging with high sampling. This instrument demonstrates the ability to detect emission from several different color centers in diamond both at the surface and internally, providing a non-destructive method to probe their 3D spatial distribution, and is currently not achievable with any other commonly used system or technique.

High-spatial density snapshot imaging spectrometer enabled by 2-photon fabricated custom fiber bundles

We report on a proof-of-concept snapshot imaging spectrometer developed using an array of optical fibers fabricated with 2-photon polymerization (2PP). The dense input array maps to an output array with engineered void spaces for spectral information. Previously, the development and fabrication of custom fiber arrays for imaging spectrometers have been a complex, time-consuming, and costly process, requiring a semi-manual assembly of commercial components. This work applies an automatic development process based on 2PP additive manufacturing with the Nanoscribe GmbH Quantum X system. The technique allows printing of arbitrary optical quality structures with submicron resolution with less than 5 nm roughness, enabling small core fibers/integrated arrays. Specifically, we developed an array prototype of 40 × 80 with 6-micron pitch at the input and 80-micron pitch at the output. The air-clad fibers had a core diameter of 5 µm. Fabricated optical fiber arrays were incorporated into a prism-based imaging spectrometer system with 48 spectral channels to demonstrate multi-spectral imaging. Imaging of a USAF target and color printed letter C as well as spectral comparisons to a commercial spectrometer were used to validate the performance of the system. These results clearly demonstrate the functionality and potential applications of the 3D-printed fiber-based snapshot imaging spectrometer.

Dual-channel snapshot imaging spectrometer with wide spectrum and high resolution

The comprehensive analysis of dynamic targets brings about the demand for capturing spatial and spectral dimensions of visual information instantaneously, which leads to the emergence of snapshot spectral imaging technologies. While current snapshot systems face major challenges in the development of wide working band range as well as high resolution, our novel dual-channel snapshot imaging spectrometer (DSIS), to the best of our knowlledge, demonstrates the capability to achieve both wide spectrum and high resolution in a compact structure. By dint of the interaction between the working band range and field of view (FOV), reasonable limits on FOV are set to avoid spectral overlap. Further, we develop a dual-channel imaging method specifically for DSIS to separate the whole spectral range into two parts, alleviating the spectral overlap on each image surface, improving the tolerance of the system for a wider working band range, and breaking through structural constraints. In addition, an optimal FOV perpendicular to the dispersion direction is determined by the trade-off between FOV and astigmatism. DSIS enables the acquisition of 53×11 spatial elements with up to 250 spectral channels in a wide spectrum from 400 to 795 nm. The theoretical study and optimal design of DSIS are further evaluated through the simulation experiments of spectral imaging.

Spatial-spectral resolution tunable snapshot imaging spectrometer: analytical design and implementation

A snapshot imaging spectrometer is a powerful tool for dynamic target tracking and real-time recognition compared with a scanning imaging spectrometer. However, all the current snapshot spectral imaging techniques suffer from a major trade-off between the spatial and spectral resolutions. In this paper, an integral field snapshot imaging spectrometer (TIF-SIS) with a continuously tunable spatial-spectral resolution and light throughput is proposed and demonstrated. The proposed TIF-SIS is formed by a fore optics, a lenslet array, and a collimated dispersive subsystem. Theoretical analyses indicate that the spatial-spectral resolution and light throughput of the system can be continuously tuned through adjusting the F number of the fore optics, the rotation angle of the lenslet array, or the focal length of the collimating lens. Analytical relationships between the spatial and spectral resolutions and the first-order parameters of the system with different geometric arrangements of the lenslet unit are obtained. An experimental TIF-SIS consisting of a self-fabricated lenslet array with a pixelated scale of 100×100 and a fill factor of 0.716 is built. The experimental results show that the spectral resolution of the system can be steadily improved from 4.17 to 0.82 nm with a data cube (N x×N y×N λ) continuously tuned from 35×35×36 to 40×40×183 in the visible wavelength range from 500 to 650 nm, which is consistent with the theoretical prediction. The proposed method for real-time tuning of the spatial-spectral resolution and light throughput opens new possibilities for broader applications, especially for recognition of things with weak spectral signature and biomedical investigations where a high light throughput and tunable resolution are needed.

Analytical design of a cemented-curved-prism based integral field spectrometer (CIFS) with high numerical aperture and high resolution

Snapshot hyperspectral imaging is superior to scanning spectrometers due to its advantage in dimensionality, allowing longer pixel dwell time and higher data cube acquisition efficiency. Due to the trade-off between spatial and spectral resolution in snapshot spectral imaging technologies, further improvements in the performance of snapshot imaging spectrometers are limited. Therefore, we propose a cemented-curved-prism-based integral field spectrometer (CIFS), which achieves high spatial and high spectral resolution imaging with a high numerical aperture. It consists of a hemispherical lens, a cemented-curved-prism and a concave spherical mirror. The design idea of aplanatic imaging and sharing-optical-path lays the foundation for CIFS to exhibit high-resolution imaging in a compact structure. The numerical model between the parameters of optical elements and the spectral resolution of the system is established, and we analyze the system resolution influenced by the hemispherical lens and the cemented-curved-prism. Thus, the refractive index requirements of the hemispherical lens and the cemented-curved-prism for the optimal spatial and spectral resolution imaging of the system are obtained, providing guidance for the construction of CIFS. The designed CIFS achieves pupil matching with a 1.8 f-number lenslet array, sampling 268 × 76 spatial points with 403 spectral channels in the wavelength band of 400 to 760 nm. The spectral and spatial resolution are further evaluated through a simulation experiment of spectral imaging based on Zemax. It paves the way for developing integral field spectrometers exhibiting high spatial and high spectral resolution imaging with high numerical aperture.

An ultra-small nine-color spectrometer with a two-layer biparted ten-dichroic-mirror array and an image sensor

An ultra-small (54 × 58 × 8.5 mm) and large aperture (1 × 7 mm) nine-color spectrometer-using an array of ten dichroic mirrors "biparted" as two layers-was developed and used for snapshot spectral imaging. Incident-light flux with a cross section smaller than the aperture size is split into nine color fluxes with 20-nm-width contiguous wavelength bands and central wavelengths of 530, 550, 570, 590, 610, 630, 650, 670, and 690 nm. Images of the nine color fluxes are simultaneously and efficiently measured by an image sensor. Unlike a conventional dichroic-mirror array, the developed dichroic-mirror array has a unique biparted configuration that not only increases the number of colors that can be measured simultaneously but also improves the image resolution of each color flux. The developed nine-color spectrometer was used for four-capillary-array electrophoresis. Eight dyes concurrently migrating in each capillary were simultaneously quantified by nine-color laser-induced fluorescence detection. Since the nine-color spectrometer is not only ultra-small and inexpensive but also has high light throughput and sufficient spectral resolution for most spectral-imaging applications, it has the potential to be widely used in various fields.

Ruggedized, field-ready snapshot light-guide-based imaging spectrometer for environmental and remote sensing applications

A field-ready, fiber-based high spatial sampling snapshot imaging spectrometer was developed for applications such as environmental monitoring and smart farming. The system achieves video rate frame transfer and exposure times down to a few hundred microseconds in typical daylight conditions with ∼63,000 spatial points and 32 spectral channels across the 470nm to 700nm wavelength range. We designed portable, ruggedized opto-mechanics to allow for imaging from an airborne platform. To ensure successful data collection prior to flight, imaging speed and signal-to-noise ratio was characterized for imaging a variety of land covers from the air. The system was validated by performing a series of observations including: Liriope Muscari plants under a range of water-stress conditions in a controlled laboratory experiment and field observations of sorghum plants in a variety of soil conditions. Finally, we collected data from a series of engineering flights and present reassembled images and spectral sampling of rural and urban landscapes.

Computational hyperspectral light-sheet microscopy

We describe a computational light-sheet microscope designed for hyperspectral acquisition at high spectral resolution. The fluorescence light emitted from the full field-of-view is focused along the entrance slit of an imaging spectrometer using a cylindrical lens. To acquire the spatial dimension orthogonal to the slit of the spectrometer, we propose to illuminate the specimen with a sequence of structured light patterns and to solve the image reconstruction problem. Beam shaping is obtained simply using a digital micromirror device in conjunction with a traditional selective plane illumination microscopy setup. We demonstrate the feasibility of this method and report the first results in vivo in hydra specimens labeled using two fluorophores.

Real-Time Hyperspectral Video Acquisition with Coded Slits

We propose a real-time hyperspectral video acquisition system that uses coded slits. Conventional imaging spectrometers usually have scanning mechanisms that reduce the temporal resolution or sacrifice the spatial resolution to acquire spectral information instantly. Recently, computational spectral imaging has been applied to realize high-speed or high-performance spectral imaging. However, the most current computational spectral imaging systems take a long time to reconstruct spectral data cubes from limited measurements, which limits real-time hyperspectral video acquisition. In this work, we propose a new computational spectral imaging system. We substitute the slit in a conventional scanning-based imaging spectrometer with coded slits, which can achieve the parallel acquisition of spectral data and thus an imaging speed that is several times higher. We also apply an electronically controlled translation stage to use different codes at each exposure level. The larger amount of data allows for fast reconstruction through matrix inversion. To solve the problem of a trade-off between imaging speed and image quality in high-speed spectral imaging, we analyze the noise in the system. The severe readout noise in our system is suppressed with S-matrix coding. Finally, we build a practical prototype that can acquire hyperspectral video with a high spatial resolution and a high signal-to-noise ratio at 5 Hz in real time.

Radiometric and design model for the tunable light-guide image processing snapshot spectrometer (TuLIPSS)

The tunable light-guide image processing snapshot spectrometer (TuLIPSS) is a novel remote sensing instrument that can capture a spectral image cube in a single snapshot. The optical modelling application for the absolute signal intensity on a single pixel of the sensor in TuLIPSS has been developed through a numerical simulation of the integral performance of each optical element in the TuLIPSS system. The absolute spectral intensity of TuLIPSS can be determined either from the absolute irradiance of the observed surface or from the tabulated spectral reflectance of various land covers and by the application of a global irradiance approach. The model is validated through direct comparison of the simulated results with observations. Based on tabulated spectral reflectance, the deviation between the simulated results and the measured observations is less than 5% of the spectral light flux across most of the detection bandwidth for a Lambertian-like surface such as concrete. Additionally, the deviation between the simulated results and the measured observations using global irradiance information is less than 10% of the spectral light flux across most of the detection bandwidth for all surfaces tested. This optical modelling application of TuLIPSS can be used to assist the optimal design of the instrument and explore potential applications. The influence of the optical components on the light throughput is discussed with the optimal design being a compromise among the light throughput, spectral resolution, and cube size required by the specific application under consideration. The TuLIPSS modelling predicts that, for the current optimal low-cost configuration, the signal to noise ratio can exceed 10 at 10 ms exposure time, even for land covers with weak reflectance such as asphalt and water. Overall, this paper describes the process by which the optimal design is achieved for particular applications and directly connects the parameters of the optical components to the TuLIPSS performance.

Research on spectral reconstruction algorithm for snapshot microlens array micro-hyperspectral imaging system

Snapshot microlens array microscopic hyperspectral imaging systems do not require a scanning process and obtain (x,y,λ) three-dimensional data cubes in one shot. Currently, the three-dimensional spectra image data are interleaved on a charge-coupled device detector, which increases subsequent data processing difficulty. The optical design software cannot simulate actual engineering installation and adjustment results accurately and the tracking results cannot guide precise rapid online calibration of the snapshot microlens array microscopic hyperspectral imaging system. To solve these problems, we propose an accurate spectral image reconstruction model based on optical tracing, derive spatial dispersion equations for the prisms and gratings, establish an algorithm model for the correspondence between the microlens array's surface dispersion spectral distribution and its imaging position, and propose a three-dimensional spectral image reconstruction algorithm. Experimental results show that this algorithm's actual spectral calibration error is better than 0.2 nm. This meets the image processing requirements of snapshot microlens array microscopic hyperspectral systems.

Snapshot Imaging Spectrometer Based on Pixel-Level Filter Array (PFA)

Snapshot spectral imaging technology plays an important role in many fields. However, most existing snapshot imaging spectrometers have the shortcomings of a large volume or heavy computational burden. In this paper, we present a novel snapshot imaging spectrometer based on the pixel-level filter array (PFA), which can simultaneously obtain both spectral and spatial information. The system is composed of a fore-optics, a PFA, a relay lens, and a monochromatic sensor. The incoming light first forms an intermediate image on the PFA through the fore-optics. Then, the relay lens reimages the spectral images on the PFA onto the monochromatic sensor. Through the use of the PFA, we can capture a three-dimensional (spatial coordinates and wavelength) datacube in a single exposure. Compared with existing technologies, our system possesses the advantages of a simple implementation, low cost, compact structure, and high energy efficiency by removing stacked dispersive or interferometric elements. Moreover, the characteristic of the direct imaging mode ensures the low computational burden of the system, thus shortening the imaging time. The principle and design of the system are described in detail. An experimental prototype is built and field experiments are carried out to verify the feasibility of the proposed scheme.

Microlens array snapshot hyperspectral microscopy system for the biomedical domain

We propose a microlens array-type snapshot hyperspectral microscope system that can provide spatial spectrum sampling according to detector frame rates for the biomedical domain. The system uses a shared optical path design. One path is used to perform direct microscopic imaging with high spatial resolution, while the other is used to collect microscopic images through a microlens array; the images are then spatially cut and reimaged such that they are spaced simultaneously by the prism-grating type hyperspectral imager's dispersion. Rapid acquisition of a three-dimensional data cube measuring 28×14×180 (x×y×λ) can be performed at the detector's frame rate. The system has a spatial resolution of 2.5 µm and can achieve 180-channel sampling of a 100 nm spectrum in the 400-800 nm spectral range with spectral resolution of approximately 0.56 nm. Spectral imaging results from biological samples show that the microlens array-type snapshot hyperspectral microscope system may potentially be applied in real-time biological spectral imaging.

Snapshot spectroscopic microscopy with double spherical slicer mirrors

Snapshot hyperspectral microscopic imaging can obtain the morphological characteristics and chemical specificity of samples simultaneously and instantaneously. We demonstrate a double-slicer spectroscopic microscopy (DSSM) that uses two spherical slicer mirrors to magnify the target image and slice it. These slits are lined up and dispersed, then mapped onto an area-array detector. An anamorphosis unit optimizes the capacity of the limited pixels. With a single shot and image recombination, a data cube can be constructed for sample analysis, and a model of DSSM is simulated. The system covers the spectral range from 500 nm to 642.5 nm with 20 spectral channels. The spatial resolution is 417 nm, and the spectral resolution is 7.5 nm.

Punching holes in light: recent progress in single-shot coded-aperture optical imaging

Single-shot coded-aperture optical imaging physically captures a code-aperture-modulated optical signal in one exposure and then recovers the scene via computational image reconstruction. Recent years have witnessed dazzling advances in various modalities in this hybrid imaging scheme in concomitant technical improvement and widespread applications in physical, chemical and biological sciences. This review comprehensively surveys state-of-the-art single-shot coded-aperture optical imaging. Based on the detected photon tags, this field is divided into six categories: planar imaging, depth imaging, light-field imaging, temporal imaging, spectral imaging, and polarization imaging. In each category, we start with a general description of the available techniques and design principles, then provide two representative examples of active-encoding and passive-encoding approaches, with a particular emphasis on their methodology and applications as well as their advantages and challenges. Finally, we envision prospects for further technical advancement in this field.

A micromirror array with annular partitioning for high-speed random-access axial focusing

Dynamic axial focusing functionality has recently experienced widespread incorporation in microscopy, augmented/virtual reality (AR/VR), adaptive optics and material processing. However, the limitations of existing varifocal tools continue to beset the performance capabilities and operating overhead of the optical systems that mobilize such functionality. The varifocal tools that are the least burdensome to operate (e.g. liquid crystal, elastomeric or optofluidic lenses) suffer from low (≈100 Hz) refresh rates. Conversely, the fastest devices sacrifice either critical capabilities such as their dwelling capacity (e.g. acoustic gradient lenses or monolithic micromechanical mirrors) or low operating overhead (e.g. deformable mirrors). Here, we present a general-purpose random-access axial focusing device that bridges these previously conflicting features of high speed, dwelling capacity and lightweight drive by employing low-rigidity micromirrors that exploit the robustness of defocusing phase profiles. Geometrically, the device consists of an 8.2 mm diameter array of piston-motion and 48-μm-pitch micromirror pixels that provide 2π phase shifting for wavelengths shorter than 1100 nm with 10-90% settling in 64.8 μs (i.e., 15.44 kHz refresh rate). The pixels are electrically partitioned into 32 rings for a driving scheme that enables phase-wrapped operation with circular symmetry and requires <30 V per channel. Optical experiments demonstrated the array's wide focusing range with a measured ability to target 29 distinct resolvable depth planes. Overall, the features of the proposed array offer the potential for compact, straightforward methods of tackling bottlenecked applications, including high-throughput single-cell targeting in neurobiology and the delivery of dense 3D visual information in AR/VR.

Single-shot ultrafast burst imaging using an integral field spectroscope with a microlens array

To fully utilize the functions of a center-wavelength-sweeping pulse train generated by a free-space angular-chirp-enhanced delay optical layout for a probe laser pulse in sequentially timed all-optical mapping photography (STAMP), we introduced an integral field spectroscopy (IFS) method using a microlens array (MLA) to produce hyperspectral images, referring to the technique as lens array (LA)-STAMP. Compared with the previous STAMP utilizing spectral filtering where a bandpass filter generated hyperspectral images, LA-STAMP achieved much higher optical throughput. In a prototype setup, we used a 60×60 MLA and demonstrated single-shot burst imaging of a femtosecond laser-induced ablation process on a glass surface with 300 ps frame intervals in a 1.8 ns time window. Each frame image was constructed by assembling spectrally dispersed 36×36 monochromatic segments distributed by each lenslet on 5×5 pixels of a CCD camera. The spatial resolution was ∼4.4µm, which was determined by the MLA's pitch and the magnification of the microscope lens. We limited the number of frames to seven in this prototype setup, although it can be scaled to ∼24 with a spatial resolution of ∼1µm by designing IFS with a fine pitch MLA.

Hyperspectral Raman Imaging Using a Spatial Heterodyne Raman Spectrometer with a Microlens Array

A new hyperspectral Raman imaging technique is described using a spatial heterodyne Raman spectrometer (SHRS) and a microlens array (MLA). The new technique enables the simultaneous acquisition of Raman spectra over a wide spectral range at spatially isolated locations within two spatial dimensions (x, y) using a single exposure on a charge-coupled device (CCD) or other detector types such as a complementary metal-oxide semiconductor (CMOS) detector. In the SHRS system described here, a 4 × 4 mm MLA with 1600, 100 µm diameter lenslets is used to image the sample, with each lenslet illuminating a different region of the SHRS diffraction gratings and forming independent fringe images on the CCD. The fringe images from each lenslet contain the fully encoded Raman spectrum of the region of the sample "seen" by the lenslet. Since the SHRS requires no moving parts, all fringe images can be measured simultaneously with a single detector exposure, and in principle using a single laser shot, in the case of a pulsed laser. In this proof of concept paper, hyperspectral Raman spectra of a wide variety of heterogeneous samples are used to characterize the technique in terms of spatial and spectral resolution tradeoffs. It is shown that the spatial resolution is a function of the diameter of the MLA lenslets, while the number of spatial elements that can be resolved is equal to the number of MLA lenslets that can be imaged onto the SHRS detector. The spectral resolution depends on the spatial resolution desired, and the number of grooves illuminated on both diffraction gratings by each lenslet, or combination of lenslets in cases where they are grouped.

A versatile, low-cost, snapshot multidimensional imaging approach based on structured light

The behaviour and function of dynamic samples can be investigated using optical imaging approaches with high temporal resolution and multidimensional acquisition. Snapshot techniques have been developed in order to meet these demands, however they are often designed to study a specific parameter, such as spectral properties, limiting their applicability. Here we present and demonstrate a frequency recognition algorithm for multiple exposures (FRAME) snapshot imaging approach, which can be reconfigured to capture polarization, temporal, depth-of-focus and spectral information by simply changing the filters used. FRAME is implemented by splitting the emitted light from a sample into four channels, filtering the light and then applying a unique spatial modulation encoding before recombining all the channels. The multiplexed information is collected in a single exposure using a single detector and extracted in post processing of the Fourier transform of the collected image, where each channel image is located in a distinct region of the Fourier domain. The approach allows for individual intensity control in each channel, has easily interchangeable filters and can be used in conjunction with, in principle, all 2D detectors, making it a low cost and versatile snapshot multidimensional imaging technique.

A background correction method to compensate illumination variation in hyperspectral imaging

Hyperspectral imaging (HSI) can measure both spatial (morphological) and spectral (biochemical) information from biological tissues. While HSI appears promising for biomedical applications, interpretation of hyperspectral images can be challenging when data is acquired in complex biological environments. Variations in surface topology or optical power distribution at the sample, encountered for example during endoscopy, can lead to errors in post-processing of the HSI data, compromising disease diagnostic capabilities. Here, we propose a background correction method to compensate for such variations, which estimates the optical properties of illumination at the target based on the normalised spectral profile of the light source and the measured HSI intensity values at a fixed wavelength where the absorption characteristics of the sample are relatively low (in this case, 800 nm). We demonstrate the feasibility of the proposed method by imaging blood samples, tissue-mimicking phantoms, and ex vivo chicken tissue. Moreover, using synthetic HSI data composed from experimentally measured spectra, we show the proposed method would improve statistical analysis of HSI data. The proposed method could help the implementation of HSI techniques in practical clinical applications, where controlling the illumination pattern and power is difficult.

Deep learning applied to hyperspectral endoscopy for online spectral classification

Hyperspectral imaging (HSI) is being explored in endoscopy as a tool to extract biochemical information that may improve contrast for early cancer detection in the gastrointestinal tract. Motion artefacts during medical endoscopy have traditionally limited HSI application, however, recent developments in the field have led to real-time HSI deployments. Unfortunately, traditional HSI analysis methods remain unable to rapidly process the volume of hyperspectral data in order to provide real-time feedback to the operator. Here, a convolutional neural network (CNN) is proposed to enable online classification of data obtained during HSI endoscopy. A five-layered CNN was trained and fine-tuned on a dataset of 300 hyperspectral endoscopy images acquired from a planar Macbeth ColorChecker chart and was able to distinguish between its 18 constituent colors with an average accuracy of 94.3% achieved at 8.8 fps. Performance was then tested on a set of images simulating an endoscopy environment, consisting of color charts warped inside a rigid tube mimicking a lumen. The algorithm proved robust to such variations, with classification accuracies over 90% being obtained despite the variations, with an average drop in accuracy of 2.4% being registered at the points of longest working distance and most inclination. For further validation of the color-based classification system, ex vivo videos of a methylene blue dyed pig esophagus and images of different disease stages in the human esophagus were analyzed, showing spatially distinct color classifications. These results suggest that the CNN has potential to provide color-based classification during real-time HSI in endoscopy.

Deep learning enabled real time speckle recognition and hyperspectral imaging using a multimode fiber array

We demonstrate the use of deep learning for fast spectral deconstruction of speckle patterns. The artificial neural network can be effectively trained using numerically constructed multispectral datasets taken from a measured spectral transmission matrix. Optimized neural networks trained on these datasets achieve reliable reconstruction of both discrete and continuous spectra from a monochromatic camera image. Deep learning is compared to analytical inversion methods as well as to a compressive sensing algorithm and shows favourable characteristics both in the oversampling and in the sparse undersampling (compressive) regimes. The deep learning approach offers significant advantages in robustness to drift or noise and in reconstruction speed. In a proof-of-principle demonstrator we achieve real time recovery of hyperspectral information using a multi-core, multi-mode fiber array as a random scattering medium.

Light-guide snapshot imaging spectrometer for remote sensing applications

A fiber-based snapshot imaging spectrometer was developed with a maximum of 31853 (~188 x 170) spatial sampling and 61 spectral channels in the 450nm-750nm range. A compact, custom-fabricated fiber bundle was used to sample the object image at the input and create void spaces between rows at the output for dispersion. The bundle was built using multicore 6x6 fiber block ribbons. To avoid overlap between the cores in the direction of dispersion, we selected a subset of cores using two alternative approaches; a lenslet array and a photomask. To calibrate the >30000 spatial samples of the system, a rapid spatial calibration method was developed based on phase-shifting interferometry (PSI). System crosstalk and spectral resolution were also characterized. Preliminary hyperspectral imaging results of the Rice University campus landscape, obtained with the spectrometer, are presented to demonstrate the system's spectral imaging capability for distant scenes. The spectrum of different plant species with different health conditions, obtained with the spectrometer, was in accordance with reference instrument measurements. We also imaged Houston traffic to demonstrate the system's snapshot hyperspectral imaging capability. Potential applications of the system include terrestrial monitoring, land use, air pollution, water resources, and lightning spectroscopy. The fiber-based system design potentially allows tuning between spatial and spectral sampling to meet specific imaging requirements.

Compact snapshot optically replicating and remapping imaging spectrometer (ORRIS) using a focal plane continuous variable filter

In this Letter, a novel snapshot spectral imaging technique, optically replicating and remapping imaging spectrometer, is presented. It is based on the combination of shifting subimages by a specially designed lenslet array (LA) and filtering subimages by a focal plane continuous variable filter (CVF). The 3D datacube is recovered by just using a simple image remapping process. The use of the LA and the focal plane CVF makes the system compact and low in cost. A handheld proof-of-principle prototype has been built and demonstrated; it covers a wavelength range of 380-860 nm with 80 spectral channels with a spatial resolution of 400×400  pixels.

Snapshot fiber spectral imaging using speckle correlations and compressive sensing

Snapshot spectral imaging is rapidly gaining interest for remote sensing applications. Acquiring spatial and spectral data within one image promotes fast measurement times, and reduces the need for stabilized scanning imaging systems. Many current snapshot technologies, which rely on gratings or prisms to characterize wavelength information, are difficult to reduce in size for portable hyperspectral imaging. Here, we show that a multicore multimode fiber can be used as a compact spectral imager with sub-nanometer resolution, by encoding spectral information within a monochrome CMOS camera. We characterize wavelength-dependent speckle patterns for up to 3000 fiber cores over a broad wavelength range. A clustering algorithm is employed in combination with l₁-minimization to limit data collection at the acquisition stage for the reconstruction of spectral images that are sparse in the wavelength domain. We also show that in the non-compressive regime these techniques are able to accurately reconstruct broadband information.

Optimization of wavelength selection for multispectral image acquisition: a case study of atrial ablation lesions

In vivo autofluorescence hyperspectral imaging of moving objects can be challenging due to motion artifacts and to the limited amount of acquired photons. To address both limitations, we selectively reduced the number of spectral bands while maintaining accurate target identification. Several downsampling approaches were applied to data obtained from the atrial tissue of adult pigs with sites of radiofrequency ablation lesions. Standard image qualifiers such as the mean square error, the peak signal-to-noise ratio, the structural similarity index map, and an accuracy index of lesion component images were used to quantify the effects of spectral binning, an increased spectral distance between individual bands, as well as random combinations of spectral bands. Results point to several quantitative strategies for deriving combinations of a small number of spectral bands that can successfully detect target tissue. Insights from our studies can be applied to a wide range of applications.

Multiplexed Optical Imaging of Tumor-Directed Nanoparticles: A Review of Imaging Systems and Approaches

In recent decades, various classes of nanoparticles have been developed for optical imaging of cancers. Many of these nanoparticles are designed to specifically target tumor sites, and specific cancer biomarkers, to facilitate the visualization of tumors. However, one challenge for accurate detection of tumors is that the molecular profiles of most cancers vary greatly between patients as well as spatially and temporally within a single tumor mass. To overcome this challenge, certain nanoparticles and imaging systems have been developed to enable multiplexed imaging of large panels of cancer biomarkers. Multiplexed molecular imaging can potentially enable sensitive tumor detection, precise delineation of tumors during interventional procedures, and the prediction/monitoring of therapy response. In this review, we summarize recent advances in systems that have been developed for the imaging of optical nanoparticles that can be heavily multiplexed, which include surface-enhanced Raman-scattering nanoparticles (SERS NPs) and quantum dots (QDs). In addition to surveying the optical properties of these various types of nanoparticles, and the most-popular multiplexed imaging approaches that have been employed, representative preclinical and clinical imaging studies are also highlighted.