Effects of phantom microstructure on their optical properties.

Significance: Developing stable, robust, and affordable tissue-mimicking phantoms is a prerequisite for any new clinical application within biomedical optics. To this end, a thorough understanding of the phantom structure and optical properties is paramount. Aim: We characterized the structural and optical properties of PlatSil SiliGlass phantoms using experimental and numerical approaches to examine the effects of phantom microstructure on their overall optical properties. Approach: We employed scanning electron microscope (SEM), hyperspectral imaging (HSI), and spectroscopy in combination with Mie theory modeling and inverse Monte Carlo to investigate the relationship between phantom constituent and overall phantom optical properties. Results: SEM revealed that microspheres had a broad range of sizes with average (13.47±5.98) µm and were also aggregated, which may affect overall optical properties and warrants careful preparation to minimize these effects. Spectroscopy was used to measure pigment and SiliGlass absorption coefficient in the VIS-NIR range. Size distribution was used to calculate scattering coefficients and observe the impact of phantom microstructure on scattering properties. The results were surmised in an inverse problem solution that enabled absolute determination of component volume fractions that agree with values obtained during preparation and explained experimentally observed spectral features. HSI microscopy revealed pronounced single-scattering effects that agree with single-scattering events. Conclusions: We show that knowledge of phantom microstructure enables absolute measurements of phantom constitution without prior calibration. Further, we show a connection across different length scales where knowledge of precise phantom component constitution can help understand macroscopically observable optical properties.

Remote Sensing Techniques: Hyperspectral Imaging and Data Analysis.

Hyperspectral imaging is a remote sensing technique that enables remote, noninvasive measurement of plant traits. Here, we outline the procedures for camera setup, scanning, and calibration, along with the acquisition of black and white reference materials, which are the key steps in collecting hyperspectral imagery. We also discuss the development of predictive models such as partial least-squares regression, using both large and small datasets, which are used to predict plant traits from hyperspectral data. To ensure practical applicability, we provide code examples that allow readers to immediately implement these techniques in real-world scenarios. We introduce these topics to beginners in an accessible and understandable manner.

P-MIRU, a Polarized Multispectral Imaging System, Reveals Reflection Information on the Biological Surface.

Reflection light forms the core of our visual perception of the world. We can obtain vast information by examining reflection light from biological surfaces, including pigment composition and distribution, tissue structure and surface microstructure. However, because of the limitations in our visual system, the complete information in reflection light, which we term 'reflectome', cannot be fully exploited. For example, we may miss reflection light information outside our visible wavelengths. In addition, unlike insects, we have virtually no sensitivity to light polarization. We can detect non-chromatic information lurking in reflection light only with appropriate devices. Although previous studies have designed and developed systems for specialized uses supporting our visual systems, we still do not have a versatile, rapid, convenient and affordable system for analyzing broad aspects of reflection from biological surfaces. To overcome this situation, we developed P-MIRU, a novel multispectral and polarization imaging system for reflecting light from biological surfaces. The hardware and software of P-MIRU are open source and customizable and thus can be applied for virtually any research on biological surfaces. Furthermore, P-MIRU is a user-friendly system for biologists with no specialized programming or engineering knowledge. P-MIRU successfully visualized multispectral reflection in visible/non-visible wavelengths and simultaneously detected various surface phenotypes of spectral polarization. The P-MIRU system extends our visual ability and unveils information on biological surfaces.

Confocal hyperspectral microscopic imager for the detection and classification of individual microalgae.

We propose a confocal hyperspectral microscopic imager (CHMI) that can measure both transmission and fluorescent spectra of individual microalgae, as well as obtain classical transmission images and corresponding fluorescent hyperspectral images with a high signal-to-noise ratio. Thus, the system can realize precise identification, classification, and location of microalgae in a free or symbiosis state. The CHMI works in a staring state, with two imaging modes, a confocal fluorescence hyperspectral imaging (CFHI) mode and a transmission hyperspectral imaging (THI) mode. The imaging modes share the main light path, and thus obtained fluorescence and transmission hyperspectral images have point-to-point correspondence. In the CFHI mode, a confocal technology to eliminate image blurring caused by interference of axial points is included. The CHMI has excellent performance with spectral and spatial resolutions of 3 nm and 2 µm, respectively (using a 10× microscope objective magnification). To demonstrate the capacity and versatility of the CHMI, we report on demonstration experiments on four species of microalgae in free form as well as three species of jellyfish with symbiotic microalgae. In the microalgae species classification experiments, transmission and fluorescence spectra collected by the CHMI were preprocessed using principal component analysis (PCA), and a support vector machine (SVM) model or deep learning was then used for classification. The accuracy of the SVM model and deep learning method to distinguish one species of individual microalgae from another was found to be 96.25% and 98.34%, respectively. Also, the ability of the CHMI to analyze the concentration, species, and distribution differences of symbiotic microalgae in symbionts is furthermore demonstrated.

Inelastic hyperspectral Scheimpflug lidar for microalgae classification and quantification.

An inelastic hyperspectral Scheimpflug lidar system was developed for microalgae classification and quantification. The correction for the refraction at the air-glass-water interface was established, making our system suitable for aquatic environments. The fluorescence spectrum of microalgae was extracted by principal component analysis, and seven species of microalgae from different phyla have been classified. It was verified that when the cell density of Phaeocystis globosa was in the range of ${{1}}{{{0}}^4}\sim{{1}}{{{0}}^6}\;{\rm{cell}}\;{\rm{m}}{{\rm{L}}^{- 1}}$, the cell density had a linear relationship with the fluorescence intensity. The experimental results show our system can identify and quantify microalgae, with application prospects for microalgae monitoring in the field environment and early warning of red tides or algal blooms.

Bedside hyperspectral imaging indicates a microcirculatory sepsis pattern - an observational study.

INTRODUCTION: Microcirculatory alterations are key mechanisms in sepsis pathophysiology leading to tissue hypoxia, edema formation, and organ dysfunction. Hyperspectral imaging (HSI) is an emerging imaging technology that uses tissue-light interactions to evaluate biochemical tissue characteristics including tissue oxygenation, hemoglobin content and water content. Currently, clinical data for HSI technologies in critical ill patients are still limited. METHODS AND ANALYSIS: TIVITA® Tissue System was used to measure Tissue oxygenation (StO2), Tissue Hemoglobin Index (THI), Near Infrared Perfusion Index (NPI) and Tissue Water Index (TWI) in 25 healthy volunteers and 25 septic patients. HSI measurement sites were the palm, the fingertip, and a suprapatellar knee area. Septic patients were evaluated on admission to the ICU (E), 6 h afterwards (E+6) and three times a day (t3-t9) within a total observation period of 72 h. Primary outcome was the correlation of HSI results with daily SOFA-scores. RESULTS: Serial HSI at the three measurement sites in healthy volunteers showed a low mean variance expressing high retest reliability. HSI at E demonstrated significantly lower StO2 and NPI as well as higher TWI at the palm and fingertip in septic patients compared to healthy volunteers. StO2 and TWI showed corresponding results at the suprapatellar knee area. In septic patients, palm and fingertip THI identified survivors (E-t4) and revealed predictivity for 28-day mortality (E). Fingertip StO2 and THI correlated to SOFA-score on day 2. TWI was consistently increased in relation to the TWI range of healthy controls during the observation time. Palm TWI correlated positively with SOFA scores on day 3. DISCUSSION: HSI results in septic patients point to a distinctive microcirculatory pattern indicative of reduced skin oxygenation and perfusion quality combined with increased blood pooling and tissue water content. THI might possess risk-stratification properties and TWI could allow tissue edema evaluation in critically ill patients. CONCLUSION: HSI technologies could open new perspectives in microcirculatory monitoring by visualizing oxygenation and perfusion quality combined with tissue water content in critically ill patients - a prerequisite for future tissue perfusion guided therapy concepts in intensive care medicine.

A Novel Hyperspectral Imaging System for Intraoperative Prediction of Cerebral Hyperperfusion Syndrome after Superficial Temporal Artery-Middle Cerebral Artery Anastomosis in Patients with Moyamoya Disease.

BACKGROUND: Postoperative cerebral hyperperfusion syndrome (CHS) may occur after superficial temporal artery (STA)-middle cerebral artery (MCA) bypass for moyamoya disease (MMD). Predicting postoperative CHS is challenging; however, we previously reported the feasibility of using a hyperspectral camera (HSC) for monitoring intraoperative changes in brain surface hemodynamics during STA-MCA bypass. OBJECTIVE: To investigate the utility of HSC to predict postoperative CHS during STA-MCA bypass for patients with MMD. METHODS: Hyperspectral images of the cerebral cortex of 29 patients with MMD who underwent STA-MCA bypass were acquired by using an HSC before and after anastomosis. We then analyzed the changes in oxygen saturation after anastomosis and assessed its correlation with CHS. RESULTS: Five patients experienced transient neurological deterioration several days after surgery. 123I-N-Isopropyl-iodoamphetamine single-photon emission computed tomography scan results revealed an intense, focal increase in cerebral blood flow at the site of anastomosis without any cerebral infarction. Patients with CHS showed significantly increased oxygen saturation (SO2) in the cerebral cortex after anastomosis relative to those without CHS (33 ± 28 vs. 8 ± 14%, p < 0.0001). Receiver operating characteristic analysis results show that postoperative CHS likely occurs when the increase rate of cortical SO2 value is >15% (sensitivity, 85.0%; specificity, 81.3%; area under curve, 0.871). CONCLUSIONS: This study indicates that hyperspectral imaging of the cerebral cortex may be used to predict postoperative CHS in patients with MMD undergoing STA-MCA bypass.

A Percutaneous Catheter for In Vivo Hyperspectral Imaging of Cardiac Tissue: Challenges, Solutions and Future Directions.

PURPOSE: Multiple studies have shown that spectral analysis of tissue autofluorescence can be used as a live indicator for various pathophysiological states of cardiac tissue, including ischemia, ablation-induced damage, or scar formation. Yet today there are no percutaneous devices that can detect autofluorescence signals from inside a beating heart. Our aim was to develop a prototype catheter to demonstrate the feasibility of doing so. METHODS AND RESULTS: Here we summarize technical solutions leading to the development of a percutaneous catheter capable of multispectral imaging of intracardiac surfaces. The process included several iterations of light sources, optical filtering, and image acquisition techniques. The developed system included a compliant balloon, 355 nm laser irradiance, a high-sensitivity CCD, bandpass filtering, and image acquisition synchronized with the cardiac cycle. It enabled us to capture autofluorescence images from multiple spectral bands within the visible range while illuminating the endocardial surface with ultraviolet light. Principal component analysis and other spectral unmixing post-processing algorithms were then used to reveal target tissue. CONCLUSION: Based on the success of our prototype system, we are confident that the development of ever more sensitive cameras, recent advances in tunable filters, fiber bundles, and other optical and computational components makes it possible to create percutaneous catheters capable of acquiring hyper or multispectral hypercubes, including those based on autofluorescence, in real-time. This opens the door for widespread use of this methodology for high-resolution intraoperative imaging of internal tissues and organs-including cardiovascular applications.

Literature review: spectral imaging applied to poultry products.

Consumption of poultry products is increasing worldwide, leading to an increased demand for safe, fresh, high-quality products. To ensure consumer safety and meet quality standards, poultry products must be routinely checked for fecal matter, food fraud, microbiological contamination, physical defects, and product quality. However, traditional screening methods are insufficient in providing real-time, nondestructive, chemical and spatial information about poultry products. Novel techniques, such as hyperspectral imaging (HSI), are being developed to acquire real-time chemical and spatial information about products without destruction of samples to ensure safety of products and prevent economic losses. This literature review provides a comprehensive overview of HSI applications to poultry products. The studies used for this review were found using the Google Scholar database by searching the following terms and their synonyms: "poultry" and "hyperspectral imaging". A total of 67 studies were found to meet the criteria. After all relevant literature was compiled, studies were grouped into categories based on the specific material or characteristic of interest to be detected, identified, predicted, or quantified by HSI. Studies were found for each of the following categories: food fraud, fecal matter detection, microbiological contamination, physical defects, and product quality. Key findings and technological advancements were briefly summarized and presented for each category. Since the first application to poultry products 20 yr ago, HSI has been shown to be a successful alternative to traditional screening methods.

Development and Evaluation of a New Spectral Disease Index to Detect Wheat Fusarium Head Blight Using Hyperspectral Imaging.

Fusarium head blight (FHB) is a major disease threatening worldwide wheat production. FHB is a short cycle disease and is highly destructive under conducive environments. To provide technical support for the rapid detection of the FHB disease, we proposed to develop a new Fusarium disease index (FDI) based on the spectral data of 374-1050 nm. This study was conducted through the analysis of reflectance spectral data of healthy and diseased wheat ears at the flowering and filling stages by hyperspectral imaging technology and the random forest method. The characteristic wavelengths selected were 570 nm and 678 nm for the late flowering stage, 565 nm and 661 nm for the early filling stage, 560 nm and 663 nm for the combined stage (combining both flowering and filling stages) by random forest. FDI at each stage was derived from the wavebands of each corresponding stage. Compared with other 16 existing spectral indices, FDI demonstrated a stronger ability to determine the severity of the FHB disease. Its determination coefficients (R2) values exceeded 0.90 and the RMSEs were less than 0.08 in the models for each stage. Furthermore, the model for the combined stage performed better when used at single growth stage, but its effect was weaker than that of the models for the two individual growth stages. Therefore, using FDI can provide a new tool to detect the FHB disease at different growth stages in wheat.

Low-cost hyper-spectral imaging system using a linear variable bandpass filter for agritech applications.

Hyperspectral imaging for agricultural applications provides a solution for non-destructive, large-area crop monitoring. However, current products are bulky and expensive due to complicated optics and electronics. A linear variable filter was developed for implementation into a prototype hyperspectral imaging camera that demonstrates good spectral performance between 450 and 900 nm. Equipped with a feature extraction and classification algorithm, the proposed system can be used to determine potato plant health with ∼88% accuracy. This algorithm was also capable of species identification and is demonstrated as being capable of differentiating between rocket, lettuce, and spinach. Results are promising for an entry-level, low-cost hyperspectral imaging solution for agriculture applications.