Development status of novel spectral imaging techniques and application to traditional Chinese medicine

Traditional Chinese medicine(TCM)is a treasure of the Chinese nation,providing effective solutions to current medical requisites.Various spectral techniques are undergoing continuous development and provide new and reliable means for evaluating the efficacy and quality of TCM.Because spectral techniques are noninvasive,convenient,and sensitive,they have been widely applied to in vitro and in vivo TCM evaluation systems.In this paper,previous achievements and current progress in the research on spectral technologies(including fluorescence spectroscopy,photoacoustic imaging,infrared thermal imaging,laser-induced breakdown spectroscopy,hyperspectral imaging,and surface enhanced Raman spectroscopy)are discussed.The advantages and disadvantages of each technology are also presented.Moreover,the future applications of spectral imaging to identify the origins,components,and pesticide residues of TCM in vitro are elucidated.Subsequently,the evaluation of the efficacy of TCM in vivo is presented.Identifying future applications of spectral imaging is anticipated to promote medical research as well as scientific and technological explorations.

Feasibility Study for Applying Spectral Imaging for Wheat Grain Authenticity Testing in Pasta

Authentication of pasta is currently determined using molecular biology-based techniques focusing on DNA as the target analyte. Whilst proven to be effective, these approaches can be criticised as being destructive, time consuming, and requiring specialist instrument training. Advances in the field of multispectral imaging (MSI) and hyperspectral imaging (HSI) have facilitated the development of compact imaging platforms with the capability to rapidly differentiate a range of materials (inclusive of grains and seeds) based on surface colour, texture and chemical composition. This preliminary investigation evaluated the applicability of spectral imaging for identification and quantitation of durum wheat grain samples in relation to pasta authenticity. MSI and HSI were capable of rapidly distinguishing between durum wheat and adulterant common wheat cultivars and assigning percentage adulteration levels characterised by low biases and good repeatability estimates. The results demonstrated the potential for spectral imaging based seed/grain adulteration testing to augment existing standard molecular approaches for food authenticity testing.

Incoherent digital holographic spectral imaging with high accuracy of image pixel registration

Fresnel incoherent correlation holography(FINCH) is a unique three-dimensional(3D) imaging technique which has the advantages of scanning-free,high resolution,and easy matching with existing mature optical systems.In this article,an incoherent digital holographic spectral imaging method with high accuracy of spectral reconstruction based on liquid crystal tunable filter(LCTF) and FINCH is proposed.Using the programmable characteristics of spatial light modulator(SLM),a series of phase masks,none of whose focal lengths changes with wavelength,is designed and made.For each wavelength of LCTF output,SLM calls three phase masks with different phase constants at the corresponding wavelength,and CCD records three holograms.The spectral images obtained by this method have a constant magnification,which can achieve pixel-level image registration,restrain image registration errors,and improve spectral reconstruction accuracy.The results show that this method can not only obtain the 3D spatial information and spectral information of the object simultaneously,but also have high accuracy of spectral reconstruction and excellent color reproducibility.

Double-AOTF-based aberration-free spectral imaging endoscopic system for biomedical applications

The problem of in vrivo photoluminescence diagnostics of the tissues acessible by endoscopes is discussed.The spectral imaging module attachable to conventional rigid and flexible medical endoscopes is developed and described.It is based on a double acousto-optical tunable filter(AOTF)and a specialized optical coupling system.The module provides wide field of view(FOV),absence of image distortions,random spectral access,fast spectral image acquisition at any wavelength in the visible range and accurate measurement of reflectance spectrum in each pixel of the image.Images of typical biomedical samples are presented and discussed.Their spectra are compared to the reference data.

Detection of illegally added drugs in dietary supplements by near-infrared spectral imaging

The application to detect ilally added drugs in dietary supplerments by near-infrared spectral imaging was studied with the focus on nifedipine,diclofenac and metformin.The method is based on near-infrared spectral images correlation cofficient to detect ilally added drugs.The results comply 100%with HPLC methods test results with no false positive results.

SPECTRAL IMAGING AND ANALYSIS TO YIELD TISSUE OPTICAL PROPERTIES

An introduction to the basics of spectral imaging as applied to biological tissues is presented.An example of a spectral image of a face is used to demonstrate the data and spectral analysis that specify the melanin content(M),blood content(B),tissue oxygen saturation(S),water content(W),fraction of scattering due to Rayleigh scattering(f)and due to Mie scattering(1−f),and the reduced scattering coefficient at 500-nm wavelength(µ
s 500 nm).The sensitivity of reflectance spectra to variation in the various parameters is illustrated.

NEAR-INFRARED,BROAD-BAND SPECTRAL IMAGING OF THE HUMAN BREAST FOR QUANTITATIVE OXIMETRY:APPLICATIONS TO HEALTHY AND CANCEROUS BREASTS

We have examined ten human subjects with a previously developed instrument for near-infrared diffuse spectral imaging of the female breast.The instrument is based on a tandem,planar scan of two collinear optical fibers(one for illumination and one for collection)to image a gently compressed breast in a transmission geometry.The optical data collection features a spatial sampling of 25 points/cm2 over the whole breast,and a spectral sampling of 2 points/nm in the 650-900nm wavelength range.Of the ten human subjects examined,eight are healthy subjects and two are cancer patients with unilateral invasive ductal carcinoma and ductal carcinoma in situ,respectively.For each subject,we generate second-derivative images that identify a network of highly absorbing structures in the breast that we assign to blood vessels.A previously developed paired-wavelength spectral method assigns oxygenation values to the absorbing structures displayed in the second-derivative images.The resulting oxygenation images feature average values over the whole breast that are significantly lower in cancerous breasts(69±14%,n=2)than in healthy breasts(85±7%,n=18)(p<0.01).Furthermore,in the two patients with breast cancer,the average oxygenation values in the cancerous regions are also significantly lower than in the remainder of the breast(invasive ductal carcinoma:49±11%vs 61±16%,p<0.01;ductal carcinoma in situ:58±8%vs 77±11%,p<0.001).

Semi-quantitative analysis on the content of berberine hydrochloride in compound berberine tablets with the fluorescence spectral imaging method

The content of berberine hydrochloride(BH)in compound berberine tablets(CBTs)is subject to strict requirements.Its content is usually measured based on chemical analysis.In this paper,the fluorescence spectral imaging method was used to study the relative content of BH from a physics perspective.By comparing the relative fluorescence intensity of self-made CBTs with di®erent mass percentages of BH,a linear positive relationship was observed between the BH content and the relative fluorescence intensity,and accordingly the quality of CBTs of different brands was evaluated.The results indicate that the fluorescence spectral imaging method can be a simple,fast and nondestructive semi-quantitative analysis method to determine the content of BH in CBTs,and this method has great potential in the quality control of CBTs.

NON-LINEAR SPECTRAL IMAGING MICROSCOPY STUDIES OF HUMAN HYPERTROPHIC SCAR

Skin scar is unique to humans,the major significant negative outcome sustained after thermal injuries,traumatic injuries,and surgical procedures.Hypertrophic scar in human skin is investigated using non-linear spectral imaging microscopy.The high contrast images and spectroscopic intensities of collagen and elastic fibers extracted from the spectral imaging of normal skin tissue,and the normal skin near and far away from the hypertrophic scar tissues in a 10-year-old patient case are obtained.The results show that there are apparent differences in the morphological structure and spectral characteristics of collagen and elastic fibers when comparing the normal skin with the hypertrophic scar tissue.These differences can be good indicators to differentiate the normal skin and hypertrophic scar tissue and demonstrate that non-linear spectral imaging microscopy has potential to noninvasively investigate the pathophysiology of human hypertrophic scar.

Spatial-Temporal Characterization of Atmospheric Aerosols via Airborne Spectral Imaging and Growing Hierarchical Self-Organizing Maps

Neural network analysis based on Growing Hierarchical Self-Organizing Map (GHSOM) is used to examine Spatial-Temporal characteristics in Aerosol Optical Depth (AOD), &Aring;ngstr&ouml;m Exponent (&Aring;E) and Precipitation Rate (PR) over selected East African sites from 2000 to 2014. The selected sites of study are Nairobi (1°S, 36°E), Mbita (0°S, 34°E), Mau Forest (0.0° - 0.6°S;35.1°E - 35.7°E), Malindi (2°S, 40°E), Mount Kilimanjaro (3°S, 37°E) and Kampala (0°N, 32.1°E). GHSOM analysis reveals a marked spatial variability in AOD and &Aring;E that is associated to changing PR, urban heat islands, diffusion, direct emission, hygroscopic growth and their scavenging from the atmosphere specific to each site. Furthermore, spatial variability in AOD, &Aring;E and PR is distinct since each variable corresponds to a unique level of classification. On the other hand, GHSOM algorithm efficiently discriminated by means of clustering between AOD, &Aring;E and PR during Long and Short rain spells and dry spell over each variable emphasizing their temporal evolution. The utilization of GHSOM therefore confirms the fact that regional aerosol characteristics are highly variable be it spatially or temporally and as well modulated by PR received over each variable.

Deep-learning based on-chip rapid spectral imaging with high spatial resolution

Spectral imaging extends the concept of traditional color cameras to capture images across multiple spectral channels and has broad ap-plication prospects.Conventional spectral cameras based on scanning methods suffer from the drawbacks of low acquisition speed and large volume.On-chip computational spectral imaging based on metasur-face filters provides a promising scheme for portable applications,but endures long computation time due to point-by-point iterative spec-tral reconstruction and mosaic effect in the reconstructed spectral im-ages.In this study,on-chip rapid spectral imaging was demonstrated,which eliminated the mosaic effect in the spectral image by deep-learning-based spectral data cube reconstruction.The experimental results show that 4 orders of magnitude faster than the iterative spec-tral reconstruction were achieved,and the fidelity of the spectral re-construction for the standard color plate was over 99%for a standard color board.In particular,video-rate spectral imaging was demon-strated for moving objects and outdoor driving scenes with good per-formance for recognizing metamerism,where the concolorous sky and white cars can be distinguished via their spectra,showing great po-tential for autonomous driving and other practical applications in the field of intelligent perception.

Differentiation of Hepatocellular Carcinoma from Hepatic Hemangioma and Focal Nodular Hyperplasia using Computed Tomographic Spectral Imaging

Background and Aims:Hepatocellular carcinoma(HCC)is the most common primary hepatic malignancy.This study was designed to investigate the value of computed tomography(CT)spectral imaging in differentiating HCC from hepatic hemangioma(HH)and focal nodular hyperplasia(FNH).Methods:This was a retrospective study of 51 patients who underwent spectral multiple-phase CT at 40–140 keV during the arterial phase(AP)and portal venous phase(PP).Slopes of the spectral curves,iodine density,water density derived from iodine-and water-based material decomposition images,iodine uptake ratio(IUR),normalized iodine concentration,and the ratio of iodine concentration in liver lesions between AP and PP were measured or calculated.Results:As energy level decreased,the CT values of HCC(n=31),HH(n=17),and FNH(n=7)increased in both AP and PP.There were significant differences in IUR in the AP,IUR in the PP,normalized iodine concentration in the AP,slope in the AP,and slope in the PP among HCC,HH,and FNH.The CT values in AP,IUR in the AP and PP,normalized iodine concentration in the AP,slope in the AP and PP had high sensitivity and specificity in differentiating HH and HCC from FNH.Quantitative CT spectral data had higher sensitivity and specificity than conventional qualitative CT image analysis during the combined phases.Conclusions:Mean CT values at low energy(40–90 keV)and quantitative analysis of CT spectral data(IUR in the AP)could be helpful in the differentiation of HCC,HH,and FNH.

Detection of endogenous foreign bodies in Chinese hickory nuts by hyperspectral spectral imaging at the pixel level

It is difficult to differentiate small,but harmful,shell fragments of Chinese hickory nuts from their kernels since they are very similar in color.Including shell fragments of Chinese hickory nuts by mistake may create safety hazards for consumers.Therefore,there is a need to develop an effective method to differentiate the shells from the kernels of Chinese hickory nuts.In this study,a deep learning approach based on a two-dimensional convolutional neural network(2D CNN)and long short-term memory(LSTM)integrated with hyperspectral imaging for distinguishing the shells and kernels of Chinese hickory nuts at the pixel level was proposed.Two classical classification methods,principal component analysis-K-nearest neighbors(PCA-KNN)and the support vector machine(SVM),were employed to establish identification models for comparison.The results showed that the 2D CNN-LSTM model achieved the best performance with an overall classification accuracy of 99.0%.Moreover,the shells in mixtures of shells and kernels were detected based on the proposed deep learning method and visualized for subsequent operations for the removal of foreign bodies.

Spatially resolved measurement of plasmon dispersion using Fourier-plane spectral imaging

We show that Fourier-plane imaging in conjunction with the Kretschmann–Raether configuration can be used for measuring polariton dispersion with spatial discrimination of the sample, over the whole visible spectral range.We demonstrate the functionality of our design on several architectures, including plasmonic waveguides, and show that our new design enables the measurement of plasmonic dispersion curves of spatially inhomogeneous structures with features as small as 3 μm, in a single shot.

About Some Aspects of Use of Optical Sensors for Monitoring the Aquatic Environment

Multi-channel polarization optical technology is increasingly used for prompt monitoring of water systems.Optical devices during the assessment of water quality determine the intensity of light through the studied aquatic environment.Spectrophotometric devices measure the spectrum of weakening of light through the aquatic environment.Spectroellipsometric devices receive spectra in vertical and horizontal polarizations.The presented article develops an adaptive optical hardware and image system for monitoring water bodies.The system is combined.It consists of 2 parts:1)automated spectrophotometer-refractometer,and 2)adaptive spectroellipsometer.The system is equipped with a corresponding algorithmic and software,including algorithms for identifying spectral curves,databases and knowledge of spectral curves algorithms for solving reverse problems.The presented system is original since it differs from modern foreign systems by a new method of spectrophotometric and spectroellipsometric measurements,an original elemental base of polarization optics and a comprehensive mathematical approach to assessing the quality of a water body.There are no rotating polarization elements in the system.Therefore,this makes it possible to increase the signal-to-noise ratio and,as a result,improve measurement stability and simplify multichannel spectrophotometers and spectroellipsometers.The proposed system can be used in various water systems where it is necessary to assess water quality or identify the presence of a certain set of chemical elements.

Stimulated Raman scattering microscopy on biological cellular machinery

Beneting from the developments of advanced optical microscopy techniques,the mysteries of biological functions at the cellular and subcellular levels have been continuously revealed.Stimulated Raman scattering(SRS)microscopy is a rapidly growing technique that has attracted broad attentions and become a powerful tool for biology and biomedicine,largely thanks to its chemical specicity,high sensitivity and fast image speed.This review paper introduces the principles of SRS,discusses the technical developments and implementations of SRS microscopy,then highlights and summarizes its applications on biological cellular machinery andnally shares our visions of potential breakthroughs in the future.

Imaging and Spectral Characteristics of Amyloid Plaque Autofluorescence in Brain Slices from the APP/PS1 Mouse Model of Alzheimer’s Disease

Amyloid deposits are one of the hallmark pathological lesions of Alzheimer's disease(AD). They can be visualized by thioflavin-S, silver impregnation,Congo red staining, and immunohistochemical reactions.However, that amyloid deposits generate blue autofluorescence(auto-F) has been ignored. Here, we report that visible light-induced auto-F of senile plaques(SPs) was detected and validated with conventional methods. Brain slices from APP/PS1(amyloid precursor protein/presenilin1) transgenic mice were mounted on slides, rinsed,coverslipped and observed for details of the imaging and spectral characteristics of the auto-F of SPs. Then the slices were treated with the above classic methods for comparative validation. We found that the SP auto-F was greatest under blue-violet excitation with a specific emission spectrum, and was much easier, more sensitive, and reliable than the classic methods. Because it does not damage slices, observation of auto-F can be combined with all post-staining techniques in slices and for brain-wide imaging in AD.

Spectroscopic detection of forest diseases:a review(1970–2020)

Sustainable forest management is essential to confront the detrimental impacts of diseases on forest ecosystems.This review highlights the potential of vegetation spectroscopy in improving the feasibility of assessing forest disturbances induced by diseases in a timely and cost-effective manner.The basic concepts of vegetation spectroscopy and its application in phytopathology are first outlined then the literature on the topic is discussed.Using several optical sensors from leaf to landscape-level,a number of forest diseases characterized by variable pathogenic processes have been detected,identified and quantified in many country sites worldwide.Overall,these reviewed studies have pointed out the green and red regions of the visible spectrum,the red-edge and the early near-infrared as the spectral regions most sensitive to the disease development as they are mostly related to chlorophyll changes and symptom development.Late disease conditions particularly affect the shortwave-infrared region,mostly related to water content.This review also highlights some major issues to be addressed such as the need to explore other major forest diseases and geographic areas,to further develop hyperspectral sensors for early detection and discrimination of forest disturbances,to improve devices for remote sensing,to implement longterm monitoring,and to advance algorithms for exploitation of spectral data.Achieving of these goals will enhance the capability of vegetation spectroscopy in early detection of forest stress and in managing forest diseases.

Dispersion control of broadband super-Rayleigh speckles for snapshot spectral ghost imaging

Snapshot spectral ghost imaging,which can acquire dynamic spectral imaging information in the field of view,has attracted increasing attention in recent years.Studies have shown that optimizing the fluctuation of light fields is essential for improving the sampling efficiency and reconstruction quality of ghost imaging.However,the optimization of broadband light fields in snapshot spectral ghost imaging is challenging because of the dispersion of the modulation device.In this study,by judiciously introducing a hybrid refraction/diffraction structure into the light-field modulation,snapshot spectral ghost imaging with broadband super-Rayleigh speckles was demonstrated.The simulation and experiment results verified that the contrast of speckles in a broad range of wavelengths was significantly improved,and the imaging system had superior noise immunity.

Virtual chromoendoscopy in small bowel capsule endoscopy: New light or a cast of shadow?

AIM: To evaluate whether virtual chromoendoscopy can improve the delineation of small bowel lesions previously detected by conventional white light small bowel capsule endoscopy(SBCE). METHODS: Retrospective single center study. One hundred lesions selected from forty-nine consecutive conventional white light SBCE(SBCE-WL) examinations were included. Lesions were reviewed at three Flexible Spectral Imaging Color Enhancement(FICE) settings and Blue Filter(BF) by two gastroenterologists with ex-perience in SBCE, blinded to each other's findings, whoranked the quality of delineation as better, equivalent or worse than conventional SBCE-WL. Inter-observer percentage of agreement was determined and analyzed with Fleiss Kappa(k) coefficient. Lesions selected for the study included angioectasias(n = 39), ulcers/ero-sions(n = 49) and villous edema/atrophy(n = 12). RESULTS: Overall, the delineation of lesions was im-proved in 77% of cases with FICE 1, 74% with FICE 2, 41% with FICE 3 and 39% with the BF, with a percent-age of agreement between investigators of 89%(k = 0.833), 85%(k = 0.764), 66%(k = 0.486) and 79%(k = 0.593), respectively. FICE 1 improved the delineation of 97.4% of angioectasias, 63.3% of ulcers/erosions and 66.7% of villous edema/atrophy with a percentage of agreement of 97.4%(k = 0.910), 81.6%(k = 0.714) and 91.7%(k = 0.815), respectively. FICE 2 improved the delineation of 97.4% of angioectasias, 57.1% of ulcers/erosions and 66.7% of villous edema/atrophy, with a percentage of agreement of 89.7%(k = 0.802), 79,6%(k = 0.703) and 91.7%(k = 0.815), respectively. FICE 3 improved the delineation of 46.2% of angioecta-sias, 24.5% of ulcers/erosions and none of the cases of villous edema/atrophy, with a percentage of agreement of 53.8% [k = not available(NA)], 75.5%(k = NA) and 66.7%(k = 0.304), respectively. The BF improved the delineation of 15.4% of angioectasias, 61.2% of ulcers/erosions and 25% of villous edema/atrophy, with a per-centage of agreement of 76.9%(k = 0.558), 81.6%(k = 0.570) and 25.0%(k = NA), respectively.CONCLUSION: Virtual chromoendoscopy can improve the delineation of angioectasias, ulcers/erosions and villous edema/atrophy detected by SBCE, with almost perfect interobserver agreement for FICE 1.