Short-wave Infrared Imaging Research Articles

The quantum revolution in vehicle sensor technology

AbstractWith technology like lidar heralding a revolution in vehicle automation, SWIR (short‐wave infrared) imaging and sensing will become increasingly vital to the automotive sector. Quantum dots, nanoscale semiconductors tunable to SWIR wavelengths, could provide the answer to empowering SWIR and bringing enhanced capability to the mass market.

Mapping water content in drying Antarctic moss communities using UAS‐borne SWIR imaging spectroscopy

AbstractAntarctic moss beds are sensitive to climatic conditions, and both their survival and community composition are particularly influenced by the availability of liquid water over summer. As Antarctic regions increasingly face climate pressures (e.g., changing hydrology and heat waves), advancing capabilities to efficiently and non‐destructively monitor water content in moss communities becomes a key research priority. Because of the complexity induced by multiple micro‐climatic drivers and its fragility, tracking the evolution and responses of moss bed moisture requires monitoring methods that are non‐intrusive, efficient, and spatially significant, such as the use of unoccupied aerial systems (UAS). In this study, we combine a multi‐species drying laboratory experiment with short‐wave infrared (SWIR) spectroscopy analyses to first develop a Random Forest regression Model (RFM) capable of predicting Antarctic moss turf water content (~5% error). The RFM was then applied to UAS‐borne SWIR imaging data (900–1700 nm, <16 nm spectral resolution) of the moss beds at high spatial resolution (2 cm) across three sites in the vicinity of Casey Station, Antarctica. The sites differed in terrain, snow cover, and moisture availability to evaluate method capabilities under different conditions. Optimum RFM parameters and input variables (spectral indices and reflectance spectra) were determined. Maps of moss moisture were validated via acquiring moss spectra and water content (using sponges inserted into the moss turf) collected in situ, for which an exponential correlation (R2 = 0.72) was reported. RFM further allowed investigation of the influential spectral variables to model water content in moss and associated spectral water absorption features. We demonstrated that UAS‐borne SWIR imaging is a promising new tool to map and quantify water content in Antarctic moss beds. Hyperspectral mapping facilitates the exploration of the spatial variability of moss health and enables the creation of a baseline against which changes in these moss communities can be measured.

Eliminating the interference of water for direct sensing of submerged plastics using hyperspectral near-infrared imager

Interference from water in the reflectance spectra of plastics is a major obstacle to optical sensing of plastics in aquatic environments. Here we present evidence of the feasibility of sensing plastics in water using hyperspectral near-infrared to shortwave-infrared imaging techniques. We captured hyperspectral images of nine polymers submerged to four depths (2.5–15 mm) in water using a hyperspectral imaging system that utilizes near-infrared to shortwave-infrared light sources. We also developed algorithms to predict the reflectance spectra of each polymer in water using the spectra of the dry plastics and water as independent variables in a multiple linear regression model after a logarithmic transformation. A narrow 1100–1300 nm wavelength range was advantageous for detection of polyethylene, polystyrene, and polyvinyl chloride in water down to the 160–320 µm size range, while a wider 970–1670 nm wavelength range was beneficial for polypropylene reflectance spectrum prediction in water. Furthermore, we found that the spectra of the other five polymers, comprising polycarbonate, acrylonitrile butadiene styrene, phenol formaldehyde, polyacetal, and polymethyl methacrylate, could also be predicted within their respective optimized wavelength ranges. Our findings provide fundamental information for direct sensing of plastics in water on both benchtop and airborne platforms.

Shortwave-infrared imaging of cancer vaccine uncovers immune response

Shortwave-infrared imaging of cancer vaccine uncovers immune response

Temperature-Dependent Modulation of Short-Wave-Infrared Light Transparency Based on Associated Structures of a Liquescent Nickel(III) Complex.

A liquescent bis(malononitriledithiolato)nickel(III) complex with a bis(methoxyethyl)imidazolium cation, 1[Ni(mnt)2 ], exhibits three-stage thermochromic modulation of transparency/absorption in the short-wave-infrared (SWIR) region (1000-2500nm), driven by associated structural changes. Upon heating, the electronic spectra of 1[Ni(mnt)2 ] in the SWIR region shift to shorter wavelengths accompanying with the solid-liquid phase transition at 76°C. Further heating to over 109°C induces a second transition of the electronic spectra, characterized by a blue-shift of the SWIR absorption in the liquid phase. The results of temperature-dependent electronic spectra and magnetic susceptibility indicated that the thermochromic changes can be attributed to the two-step dissociation of the associated structures of [Ni(mnt)2 ]- , occurring during the solid-liquid phase transition and the shift of dimer-monomer equilibrium in the liquid state. These changes can be visualized using an SWIR imaging camera under appropriate SWIR lights.

Shortwave Infrared Polarization Imaging and Monolithic Integrated Polarization Amplification Systems Based on Aligned Carbon Nanotube Arrays

AbstractNext‐generation shortwave infrared (SWIR) imaging systems generally require a multidimensional information sensing capability (including intensity, wavelength, polarization, phase, etc.), a highly integrated photodetector unit, and information processing, allowing for miniaturization and low‐cost production. However, traditional polarized SWIR imaging systems with integrated polarizer arrays as supplementary filters and silicon‐based amplifying circuits are complicated and very expensive. Here, a SWIR polarization‐sensitive photodetector and a monolithic integrated polarization amplification system (MIPAS) based on well‐aligned carbon nanotube (CNT) arrays are demonstrated. The polarization‐sensitive CNT photodetector exhibits anisotropic ratios of ≈5.18 and ≈7.56 at 1800 and 2000 nm wavelengths, respectively, and high‐resolution characteristics that can be utilized to image SWIR laser spots with a radius of less than 10 µm. Furthermore, MIPAS including a CNT field‐effect transistor, a CNT loading resistor, and a polarization‐sensitive CNT photodetector is used to increase the anisotropic ratio of the CNT photodetector. The amplified anisotropic ratio is improved up to 173 and 243 at 1800 and 2000 nm wavelengths, respectively, which is the maximum reported in the SWIR band. Our work demonstrates that the CNT polarization‐sensitive photodetector has the potential for SWIR polarization imaging with a monolithic integrated polarization amplification system.

Short-wave infrared fluorescence imaging of near-infrared dyes with robust end-tail emission using a small-animal imaging device.

Commercially available near-infrared (NIR) dyes, including indocyanine green (ICG), display an end-tail of the fluorescence emission spectrum detectable in the short-wave infrared (SWIR) window. Imaging methods based on the second NIR spectral region (1,000-1,700 nm) are gaining interest within the biomedical imaging community due to minimal autofluorescence and scattering, allowing higher spatial resolution and depth sensitivity. Using a SWIR fluorescence imaging device, the properties of ICG vs. heptamethine cyanine dyes with emission >800 nm were evaluated using tissue-simulating phantoms and animal experiments. In this study, we tested the hypothesis that an increased rigidity of the heptamethine chain may increase the SWIR imaging performance due to the bathochromic shift of the emission spectrum. Fluorescence SWIR imaging of capillary plastic tubes filled with dyes was followed by experiments on healthy animals in which a time series of fluorescence hindlimb images were analyzed. Our findings suggest that higher spatial resolution can be achieved even at greater depths (>5 mm) or longer wavelengths (>1,100 nm), in both tissue phantoms and animals, opening the possibility to translate the SWIR prototype toward clinical application.

Rapid Detection of Single- and Co-Contaminant Aflatoxins and Fumonisins in Ground Maize Using Hyperspectral Imaging Techniques

Aflatoxins and fumonisins, commonly found in maize and maize-derived products, frequently co-occur and can cause dangerous illness in humans and animals if ingested in large amounts. Efforts are being made to develop suitable analytical methods for screening that can rapidly detect mycotoxins in order to prevent illness through early detection. A method for classifying contaminated maize by applying hyperspectral imaging techniques including reflectance in the visible and near-infrared (VNIR) and short-wave infrared (SWIR) regions, and fluorescence was investigated. Machine learning classification models in combination with different preprocessing methods were applied to screen ground maize samples for naturally occurring aflatoxin and fumonisin as single contaminants and as co-contaminants. Partial least squares–discriminant analysis (PLS-DA) and support vector machine (SVM) with the radial basis function (RBF) kernel were employed as classification models using cut-off values of each mycotoxin. The classification performance of the SVM was better than that of PLS-DA, and the highest classification accuracies for fluorescence, VNIR, and SWIR were 89.1%, 71.7%, and 95.7%, respectively. SWIR imaging with the SVM model resulted in higher classification accuracies compared to the fluorescence and VNIR models, suggesting that as an alternative to conventional wet chemical methods, the hyperspectral SWIR imaging detection model may be the more effective and efficient analytical tool for mycotoxin analysis compared to fluorescence or VNIR imaging models. These methods represent a food safety screening tool capable of rapidly detecting mycotoxins in maize or other food ingredients consumed by animals or humans.

On-Demand Control of Short-Wave Infrared Light Transparency Based on Stimuli-Responsive Association of Tetrathiafulvalene Radical Cation.

The light-transmissive properties of a solid-state tetrathiafulvalene radical cation-bis(trifluoromethanesulfonyl)imide, 1-C5•+•NTf2-, underwent instantaneous changes in the short-wave infrared (SWIR) region (1000-2500 nm) due to upon exposure to solvent vapor or the application of mechanostress at room temperature. The initial solid state of 1-C5•+•NTf2- exhibited strong absorption in the near-infrared (NIR; 700-1000 nm) and SWIR regions, whereas the absorption in the SWIR region was significantly diminished in the stimulated state induced by dichloromethane vapor. Upon cessation of vapor stimulation, the solid state spontaneously and promptly reverted to its original state, characterized by absorption bands in the NIR/SWIR region. Moreover, the SWIR absorption was absent upon the application of mechanical stress using a steel spatula. The reversal was fast and occurred within 10 s. These changes were visualized using a SWIR imaging camera under 1450-nm light irradiation. Experimental investigations demonstrated that the transparency to the SWIR light in the solid states was modulated through significant structural transformations of the associated radical cations, with transitions between columnar and isolated π-dimer structures under ambient and stimulated conditions, respectively.

On‐Demand Control of Short‐Wave Infrared Light Transparency Based on Stimuli‐Responsive Association of Tetrathiafulvalene Radical Cations

AbstractThe light‐transmissive properties of a solid‐state tetrathiafulvalene radical cation‐bis(trifluoromethanesulfonyl)imide, 1‐C5⋅+ ⋅ NTf2−, underwent instantaneous changes in the short‐wave infrared (SWIR) region (1000–2500 nm) upon exposure to solvent vapor or the application of mechanostress at room temperature. The initial solid state of 1‐C5⋅+ ⋅ NTf2− exhibited strong absorption in the near‐infrared (NIR; 700–1000 nm) and SWIR regions, whereas the absorption in the SWIR region was significantly diminished in the stimulated state induced by dichloromethane vapor. Upon cessation of vapor stimulation, the solid state spontaneously and promptly reverted to its original state, characterized by absorption bands in the NIR/SWIR region. Moreover, the SWIR absorption was absent upon the application of mechanical stress using a steel spatula. The reversal was fast and occurred within 10 s. These changes were visualized using a SWIR imaging camera under 1450‐nm light irradiation. Experimental investigations demonstrated that the transparency to the SWIR light in the solid states was modulated through significant structural transformations of the associated radical cations, with transitions between columnar and isolated π‐dimer structures under ambient and stimulated conditions, respectively.

Evaluating the Performance of PRISMA Shortwave Infrared Imaging Sensor for Mapping Hydrothermally Altered and Weathered Minerals Using the Machine Learning Paradigm

Satellite images provide consistent and frequent information that can be used to estimate mineral resources over a large spatial extent. Advances in spaceborne hyperspectral remote sensing (HRS) and machine learning can help to support various remote-sensing-based applications, including mineral exploration. Leveraging these advances, the present study evaluates recently launched PRISMA spaceborne satellite images to map hydrothermally altered and weathered minerals using various machine-learning-based classification algorithms. The study was performed for the town of Jahazpur in Rajasthan, India (75°06′23.17″E, 25°25′23.37″N). The distribution map for minerals such as kaolinite, talc, and montmorillonite was generated using the spectral angle mapper technique. The resultant mineral distribution map was verified through an intensive field validation survey on surface exposures of the minerals. Furthermore, the obtained pixels of the end-members were used to develop the machine-learning-based classification models. Measures such as accuracy, kappa coefficient, F1 score, precision, recall, and ROC curve were employed to evaluate the performance of developed models. The results show that the stochastic gradient descent and artificial-neural-network-based multilayer perceptron classifiers were more accurate than other algorithms. Results confirm that the PRISMA dataset has enormous potential for mineral mapping in mountainous regions utilizing a machine-learning-based classification framework.

72 Multi-Spectral SWIR Imaging in Humans Reveals Correlations with Distinct Skin Burn Depths

Abstract Introduction Burn depth determination is a critical aspect of burn patient care but currently lacks accuracy in clinical practice. We have shown first in animal models and then in a two-patient characterization that Short Wave Infrared (SWIR) imaging, which penetrates tissue better than visual or near-infrared light and is very sensitive to water content, can distinguish between superficial and deep tissue necrosis. Here we present the findings from our pilot study of 10 patients showing the use of multi-spectral SWIR imaging of human burn injury as a potential technique for burn depth determination. Methods Ten patients admitted for mixed depth thermal injuries between 5-40% TBSA were analyzed using our SWIR assessment tool. Prior to burn excision the SWIR system was used to image burn areas and normal skin at 4 different SWIR wavelengths (Figure 1A). Standard photographs from imaged areas were collected and presented for 5 independent, blinded, surgeons’ assessments. Using the visual and SWIR images, 5-15 regions of interest (ROI) were selected from each of the burned areas and normalized to adjacent normal skin and the reflected light intensity in each ROI was averaged at each wavelength. Statistics were done using Mann-Whitney U tests. Results Visual and SWIR images were collected from burn areas in 10 patients for a total of 273 burn ROIs. The ROIs were assessed by the surgeons with ROIs being agreed upon as being superficial or superficial partial thickness (SPT) (n=47), deep partial thickness (DPT) (n=97), or full thickness (FT) (n=129) burns by a majority (60% or above) consensus. As seen in Figure 1B, the reflectance intensities (RIs) from superficial and SPT burns were significantly different than the DPT burns at the 1940 nm wavelength (p=0.05) and significantly different than FT burns at 1200 nm (p=0.008) and 1940 nm (p=0.009). When DPT and FT burns were compared there was a significant difference a 1200 nm (p=0.003) and 2250 nm (p=0.01). Conclusions Here we present a 10 patient SWIR pilot study demonstrating distinct ROIs of SWIR wavelengths for different burn depths based on consensus surgeon assessments. Overall, as burn depth increases, the 1200 and 2250 nm wavelengths show increasing RIs and 1940 nm show decreasing RIs. These results motivate further studies of SWIR imaging including pending histological analysis in the hope to non-invasively and accurately identify operative versus non-operative burns. Applicability of Research to Practice This new SWIR technology may enable us to more objectively assess burn depth, leading to improved surgical decision making and better patient outcomes.

Tex Se1- x Photodiode Shortwave Infrared Detection and Imaging.

Short-wave infrared detectors are playing an increasingly important role in the fields of autonomous driving, food safety, disease diagnosis and scientific research. However, the mature short-wave infrared camera such as InGaAs has the disadvantage of complexly heterogeneous integration with complementary metal-oxide-semiconductor (CMOS) readout circuits, leading to high cost and low imaging resolution. Herein, we report a low-cost, high-performance, and high-stability Tex Se1- x short-wave infrared photodiode detector. The Tex Se1- x thin film is fabricated through CMOS-compatible low-temperature evaporation and post-annealing process, showcasing the potential of direct integration on the readout circuit. The device demonstrates a broad-spectrum response of 300-1600nm, a room-temperature specific detectivity of 1.0 × 1010 Jones, a -3dB bandwidth up to 116kHz, and a linear dynamic range of over 55dB, achieving the fastest response among Te-based photodiode devices and a dark current density 7 orders of magnitude smaller than Te-based photoconductive and field-effect transistor devices. With a simple Si3 N4 packaging, the detector shows high electric stability and thermal stability, meeting the requirements for vehicular applications. Based on the optimized Tex Se1- x photodiode detector, we demonstrate the applications in material identification and masking imaging. Our work paves a new way for CMOS-compatible infrared imaging chips. This article is protected by copyright. All rights reserved.

Multiblock spectral imaging for identification of pre-harvest sprouting in Hordeum vulgare

A novel data fusion method based on the use of visible/near-infrared (VNIR) and shortwave infrared (SWIR) imaging sensors, to distinguish between pregerminated and ungerminated barley grain is proposed. Spectral imaging was used to fingerprint germinated and ungerminated barley grain from a total of 5640 average spectra representing single barley kernels varying with respect to germination time. Chemometric approaches utilising partial least squares-discriminant analysis (PLS-DA) and multiblock sequential and orthogonalized partial least squares-linear discriminant analysis (SO-PLS-LDA) and sequential and orthogonalized covariance selection-linear discriminant analysis (SO-CovSel-LDA) were used to build classification models. SO-PLS-LDA achieved a total classification rate of 99.88%, while SO-CovSel-LDA resulted in a classification accuracy of 97.46% when a maximum of 8 variables were selected from each data block (VNIR and SWIR) – models were validated on an independent test set. The use of multiblock approaches led to increased prediction accuracy, compared to PLS-DA, and a viable solution to address the industry problem to detect pregerminated malting barley in a rapid, non-destructive manner. This represents a significant advance with respect to the current dated methods which are hindered by time-consuming wet chemistry techniques and human subjective bias. The potential of the proposed new technique also has the further advantage of moving toward multispectral systems which can be used to detect pre-harvest germinated barley using an even more computationally rapid and affordable online sorting machine incorporating the wavebands of importance selected by SO-CovSel-LDA. The study highlights how sequential and orthogonalised data fusion approaches, in the food and agricultural sector, are powerful solutions to real world problems.

Enhancing intraoperative tumor delineation with multispectral short-wave infrared fluorescence imaging and machine learning.

Fluorescence-guided surgery (FGS) provides specific real-time visualization of tumors, but intensity-based measurement of fluorescence is prone to errors. Multispectral imaging (MSI) in the short-wave infrared (SWIR) has the potential to improve tumor delineation by enabling machine-learning classification of pixels based on their spectral characteristics. Determine whether MSI can be applied to FGS and combined with machine learning to provide a robust method for tumor visualization. A multispectral SWIR fluorescence imaging device capable of collecting data from six spectral filters was constructed and deployed on neuroblastoma (NB) subcutaneous xenografts ( ) after the injection of a NB-specific NIR-I fluorescent probe (Dinutuximab-IRDye800). We constructed image cubes representing fluorescence collected from to 1450nm and compared the performance of seven learning-based methods for pixel-by-pixel classification, including linear discriminant analysis, -nearest neighbor classification, and a neural network. The spectra of tumor and non-tumor tissue were subtly different and conserved between individuals. In classification, a combine principal component analysis and -nearest-neighbor approach with area under curve normalization performed best, achieving 97.5% per-pixel classification accuracy (97.1%, 93.5%, and 99.2% for tumor, non-tumor tissue and background, respectively). The development of dozens of new imaging agents provides a timely opportunity for multispectral SWIR imaging to revolutionize next-generation FGS.

Shortwave Infrared Imaging Enables High-Contrast Fluorescence-Guided Surgery in Neuroblastoma.

Multispectral near-infrared I/shortwave infrared fluorescence imaging is a versatile system enabling high tumor-to-background signal for safer and more complete resection of pediatric tumors during surgery.

High-Performance Shortwave Infrared Detector Based on Multilayer Carbon Nanotube Films.

Carbon nanotube (CNT) is an ideal candidate material for shortwave infrared (SWIR) detectors due to its large band gap tunability, strong infrared light absorption, and high mobility. Furthermore, the photodetectors based on CNT can be prepared on any substrate using a low-temperature process, which is conducive to three-dimensional (3D) integration. However, owing to the absorption limitation (<2%) of a single-layer network CNT film with low density, the photodetectors of CNT film show low photocurrent responsivity and detectivity. In this paper, we optimize the thickness of the high-purity semiconducting network CNT films to increase the photocurrent responsivity of the photodetectors. When the thickness of network CNT film is about 5 nm, the responsivity of the zero-bias voltage can reach 32 mA/W at 1800 nm wavelength. Then, using stacked CNT films and contact electrode design, the photodetectors exhibit a maximum responsivity of 120 mA/W at 1800 nm wavelength. The photodetectors with stacked CNT films and local n-type channel doping demonstrated a wide response spectral range of 1200-2100 nm, a peak detectivity of 3.94 × 109 Jones at room temperature, and a linear dynamic range over 118 dB. Moreover, the peak detectivity is over 2.27 × 1011 Jones when the temperature is 180 K. Our work demonstrates the potential of the CNT film for future SWIR imaging at a low cost.

Assessment of the activity of secondary caries lesions with short-wavelength infrared, thermal, and optical coherence tomographic imaging.

Significance: Leakage in the interfaces between restorative materials and tooth structure allows for fluid and bacterial acid infiltration, causing restoration failure due to secondary caries. Dentists spend more time replacing composite restorations than placing new ones. Previous in vitro and in vivo studies on enamel and root surfaces using shortwave-infrared (SWIR) and thermal imaging during dehydration with forced air have been promising for assessing lesion activity. Aim: We hypothesized that SWIR reflectance and thermal imaging methods can be used to monitor the activity of secondary caries lesions around composite restorations. The objective of this study was to employ these methods to measure the rate of fluid loss from lesions during dehydration with forced air to assess lesion activity. Approach: Sixty-three extracted human teeth with total of 109 suspected secondary lesions were examined using SWIR and thermal imaging during dehydration. The thickness of the highly mineralized transparent surface layer (TSL) at lesion interfaces indicative of lesion activity was measured by optical coherence tomography (OCT). Micro-computed tomography (MicroCT) was used to further confirm lesion severity and structure. OCT and MicroCT measurements of lesion structure, depth, and severity were correlated with fluid loss rates measured with SWIR reflectance and thermal imaging. Results: TSL thickness measured with OCT correlated with both SWIR reflectance and thermal measurements of rates of fluid loss ( ). Increasing TSL thickness led to decreased permeability of lesions, potentially indicating full lesion arrest at . SWIR performed better than thermal imaging for secondary lesion activity assessment, although both methods performed best on smooth surface lesions. Conclusions: Nondestructive SWIR reflectance and OCT imaging methods are promising for clinically monitoring the activity of secondary caries lesions.

Voltage-dependent extended shortwave infrared (e-SWIR) photodetection-band tuning utilizing the Moss–Burstein effect

Extended shortwave infrared (e-SWIR) photodetectors and imaging focal plane arrays covering the wavelength beyond the conventional In0.53Ga0.47As cutoff wavelength of 1.65 micrometers (µm) can find numerous applications in infrared sensing and imaging. This paper reports voltage-tunable e-SWIR photodetectors based on the conventional gallium antimonide (GaSb) n–i–p and p–i–n homojunctions on GaSb substrates, which offer bias-dependent photodetection band tuning with a simple structure and high material crystal quality due to the perfect lattice matching on the substrates. Detection bands between the cutoff wavelengths of 1.7 µm and 1.9 µm can be tuned with a low reverse bias voltage of <0.1 volts (V). The mechanism of the voltage-dependent band-tuning was analyzed and attributed to the Moss–Burstein effect, which changes the electron and hole filling factors under different reverse bias voltages. This analysis agreed with the experimental data. The Moss–Burstein effect-induced voltage-dependent band-tuning mechanism can provide useful guidance for the designs of e-SWIR photodetectors.

Deep-tissue SWIR imaging using rationally designed small red-shifted near-infrared fluorescent protein.

Applying rational design, we developed 17 kDa cyanobacteriochrome-based near-infrared (NIR-I) fluorescent protein, miRFP718nano. miRFP718nano efficiently binds endogenous biliverdin chromophore and brightly fluoresces in mammalian cells and tissues. miRFP718nano has maximal emission at 718 nm and an emission tail in the short-wave infrared (SWIR) region, allowing deep-penetrating off-peak fluorescence imaging in vivo. The miRFP718nano structure reveals the molecular basis of its red shift. We demonstrate superiority of miRFP718nano-enabled SWIR imaging over NIR-I imaging of microbes in the mouse digestive tract, mammalian cells injected into the mouse mammary gland and NF-kB activity in a mouse model of liver inflammation.