Development and performance validation of a low-cost algorithms-based hyperspectral imaging system for radiodermatitis assessment.

We report a spectrally and temporally programmable light engine based on a spatial light modulator that can dynamically create any narrow or broadband spectral profile for hyperspectral, fluorescence, or principal component imaging. Most hyperspectral or multispectral imaging systems use wavelength selection devices such as acousto-optic tunable filters (AOTFs), tunable grating or prism-based monochromators, or filter wheels. While these devices can select wavelengths they cannot create arbitrary spectral profiles. This simple and economical system can be controlled at high speed (up to 5000 illumination profiles per second). Digitally controlled illumination is bit additive with image data providing high dynamic range imaging with monochrome or color imaging devices. This is especially advantageous for endoscopes employing small well CCD or CMOS sensors since the dynamic range now can extend beyond the limits of the sensor itself. In this report we show multispectral images of in vivo tissue and in vitro tissue samples using endoscopes, surgical microscopes and conventional microscopes.

Canopy imaging offers a non-destructive, efficient way to objectively measure canopy size, detect stress symptoms, and assess pigment concentrations. While it is faster and easier than traditional destructive methods, manual image analysis, including segmentation and evaluation, can be time-consuming. To make imaging more widely accessible, it’s essential to reduce the cost of imaging systems and automate the analysis process. We developed a low-cost imaging system with automated analysis using an embedded microcomputer equipped with a monochrome camera and a filter for a total hardware cost of ~USD 500. Our imaging system takes images under blue, green, red, and infrared light, as well as chlorophyll fluorescence. The system uses a Python-based program to collect and analyze images automatically. The multi-spectral imaging system separates plants from the background using a chlorophyll fluorescence image, which is also used to quantify canopy size. The system then generates normalized difference vegetation index (NDVI, “greenness”) images and histograms, providing quantitative, spatially resolved information. We verified that these indices correlate with leaf chlorophyll content and can easily add other indices by installing light sources with the desired spectrums. The low cost of the system can make this imaging technology widely available.

In recent years, endoscopic imaging has become the major diagnostic approach for early cancer. It is difficult to accurately obtain the information of lesions and components content by using conventional white light imaging (C-WLI). Multispectral imaging techniques such as narrowband imaging are widely used in endoscopic clinical because of their specificity on the surface structure of digestive tract mucosa. However, there is still a lack of multispectral techniques for tissue components specificity. Tissue components such as lipid, hemoglobin are closely related to the generation and development of tumors, but it is difficult to observe the characteristics of lipid and hemoglobin by conventional white light imaging. Therefore, we studied the multispectral endoscopic imaging technique for the analysis of digestive tract mucosal components. Based on the reflectance spectrum characteristics of these tissue components, we determined their specific wavelength, and comprehensively considered the absorption, scattering, oxygenation and others in order to determine the most appropriate optical band in the wavelength range of 365-660nm. Through experimental verification, we choose different narrow-band wavelength combinations for lipids and hemoglobin oxygen saturation respectively to achieve multispectral imaging. In order to simulate the optical properties of digestive tract surface, we made tissue optical phantom. At the same time, we tested and optimized the imaging system and algorithm by the experiments in vitro, and obtained the optimal multispectral image of tissue components, then realize the quantitative detection combined with the content analysis algorithm. Our pilots show that the multispectral imaging system can improve the contrast of endoscopy image, enhance the detail information, achieve high precision detection of tissue components content, and control the error within 10%.

A low-cost multispectral imaging system for the characterisation of soil and small vegetation properties using visible and near-infrared reflectance

Chapter 5 - Hyperspectral imaging applications

A five-band multispectral(MIS)imaging system has been constructed and tested by the Hughes Research Laboratories. It has five boresighted sensors mounted on a scanning pedestal in a completely mobile and self-contained instrumentation trailer. The systems are .8μ passive, 1.06μ active/ranging, 10.6μ active, 8-12μ passive and 95 GHz (3.2 mm) active/ranging. The MIS operates in all weather conditions and produces registered, calibrated and digitized 12-bit raster scanned imagery. Designed as a sensor test bed for DARPA, the MIS is a versatile and adaptable system, which has potential use for a wide range of imaging and non-imaging applications. Field tests conducted in Culver City, California and Climax, Colorado will be discussed and the applicability of the MIS to the acquisition and analysis of more diverse scenes will be discussed.

Multispectral imaging technique has been used for skin analysis, especially for in-vivo non contact mapping of skin's chromophores. It is implemented by analyzing spectral cube data, i.e. a spatial image data that are taken at different wavelength. The acquired cube data is then used to construct 2-D maps of the distributed concentrations of chromophores, i.e. oxy-/deoxy-haemoglobin and melanin. The developmental goal of measurement device is to help dermatologist with an accurate tool for perform analysis on patient's skin condition. In this paper efforts to develope and characterize a new multispectral imaging (MSI) system for dermatology application will be described. The system developed system is operated using 12 wavelengths between 350 and 970 nm, at an equally wavelength intervals. The system composed of two parts: i.e. a) the light source, constructed using LEDs with 12 different wavelenghts in an dome-shaped compartment, and b) a monochromatic 8-Bit CCD camera, equipped with C-Mount objective lens, for capturing skin images under different illuminating wavelengths. A dedicated software to control the system, i.e. for acquired and processing multispectral images, were developed based on GUI MATLAB. Characterization were done to examined the inherent properties of the developed multispectral system, both for the light source (spectral bands of the LEDs used) and for the camera (spatial uniformity, linearity, and resolution). The multispectral imaging system is capable to construct 2-D map of distributed concentrations of chromophores from a skin surface in less than 6 seconds, which is regarded as suitable for daily clinical practice.

Most recent bidirectional reflectance distribution function (BRDF) measurement systems are the image-based that consist of a light source, a detector, and curved samples. They are useful for measuring the reflectance properties of a material but they have two major drawbacks. They suffer from high cost of BRDF acquisition and also give inaccurate results due to the limited use of spectral bands. In this paper, we propose a novel multispectral HDR imaging system and its efficient characterization method. It combines two promising technologies: high dynamic range (HDR) imaging and multispectral imaging to measure BRDF. We perform a full spectral recovery using camera response curves for each wavelength band and its analysis. For this, we use an HDR camera to capture HDR images and a liquid crystal tunable filter (LCTF) to generate multi-spectral images. Our method can provide an accurate color reproduction of metameric objects as well as a saturated image. Our multi-spectral HDR imaging system provides a very fast data acquisition time and also gives a low system setup cost compared to previous multi-spectral imaging systems and point-based commercial spectroradiometers. We verify the color accuracy of our multi-spectral HDR imaging system in terms of human vision and metamerism using colorimetric and spectral metric.

Multispectral imaging, which extends the number of imaging channels beyond the conventional three, has demonstrated to be beneficial for a wide range of applications. Its ability of acquiring images beyond the visible range and applicability in many different application domains lead to the design and the development of a number of multispectral imaging technologies and systems. Given different systems to choose from, it is important to be able to compare them in a general and in many situations specific to a certain application of interest. In this paper, we evaluate several conventional and recently proposed multispectral imaging systems, both qualitatively and quantitatively. Both spectral and colorimetric accuracies are used as the criteria in the quantitative evaluation. The systems are evaluated and compared for two specific applications: imaging of natural scenes and paintings (cultural heritage), as well as for a general spectral imaging solution. This work provides a framework for the evaluation and comparison of different multispectral imaging systems, which we believe, would be very helpful in identifying the most appropriate technique or system for a given application.

Multispectral imaging systems with selected bands can commonly be used for real-time applications of food processing. Recent research has demonstrated several image processing methods including binning, noise removal filter, and appropriate morphological analysis in real-time mode can remove most false positive/negative errors. Recently researchers developed a real-time hyperspectral imaging platform that has the ability for multi-tasking during food processes. Such a system can be installed at different locations on a food processing line to solve significant food safety problems such as disease and contaminant detection simultaneously. Real-time food inspection with a developed line-scan hyperspectral imaging system is possible, with abilities of data binning utilizing a random track mode of the EMCCD sensor, and the custom software supporting multitasks. The recent development of a line-scan hyperspectral imaging system for real-time multispectral imaging applications for the food industry is demonstrated. The real-time hyperspectral imaging system consists of a spectrograph, EMCCD camera, and real-time image processing software. The imaging system can be easily modified for other real-time food inspection applications, with simple parameter changes in the software during processing. The real-time image processing software architecture is based on the ping pong memory, and a circular buffer for the multitasking of image grabbing and processing. An image-based internal triggering (i.e. polling) algorithm is developed to determine the start and end positions of objects with Microsoft Visual C++ environment.

Spectral imaging including machine vision and multispectral imaging can provide a rapid, nondestructive means to assess agricultural commodities for their quality and safety for human consumption. These nondestructive techniques generally rely on reflectance measurements; the most commonly used spectral regions range through the visible (Vis) to the near infrared (NIR). Another optical sensing technique is based on fluorescence that is generally regarded as more sensitive optical sensing tools compared to reflectance techniques. Recently, we developed two imaging systems for food safety research; a laboratory-based hyperspectral imaging system capable of both reflectance and fluorescence measurements and a multispectral laser induced fluorescence imaging system. Because many contiguous spectral bands are acquired with each hyperspectral image pixel, the resulting data quantity makes uses of hyperspectral imaging spectrometer for on-line food safety inspection impractical. Instead, the spectral and spatial information is used to determine several optimal wavebands that can be implemented to a multispectral imaging system. We present a systematic method for using hyperspectral image data to identify few wavebands to be used in multispectral detection systems. Also presented is a two-band ratio as a multispectral fusion method along with automated detection for animal feces contamination on apples. The fluorescence imaging techniques demonstrated that even minute animal feces, not clearly visible to human eye, could be detected. Practical considerations for development of multispectral fluorescence imaging systems for on-line uses are also discussed.

An accurate characterization method for a multispectral high-dynamic-range (HDR) imaging system is proposed by combining multispectral and HDR imaging technologies. The multispectral HDR imaging system, which can acquire the visible spectrum at many wavelength bands, can provide an accurate color reproduction and physical radiance information of real objects. An HDR camera is used to capture an HDR image without multiple exposures and a liquid crystal tunable filter (LCTF) is used to generate multispectral images. Due to its several limitations in the multispectral HDR imaging system, a carefully designed and an innovative characterization algorithm is presented by considering a logarithmic camera response of the HDR camera and different spectral transmittance of the LCTF. The proposed method efficiently and accurately recovers the full spectrum from the multispectral HDR images using a transformation matrix and provides device-independent color information (e.g., CIEXYZ and CIELAB). The transformation matrix is estimated by training the estimated sensor responses from a multispectral HDR imaging system and the reflectance measurements from a spectroradiometer using Moore–Penrose pseudoinverse matrix.

A simultaneous multispectral fluorescence imaging system incorporating multiplexed volume holographic grating (VHG) is developed to acquire multispectral images of an object in one shot. With the multiplexed VHG, the imaging system can provide the distribution and spectral characteristics of multiple fluorophores in the scene. The implementation and performance of the simultaneous multispectral imaging system are presented. Further, the system’s capability in simultaneously obtaining multispectral fluorescence measurements is demonstrated with in vivo experiments on a mouse. The demonstrated imaging system has the potential to obtain multispectral images fluorescence simultaneously.

Thermal-pulse method is a powerful tool for measuring space charge distributions in polymer films. The data analysis for thermal-pulse method involves the Fredholm integral equation of the first kind, which requires an appropriate numerical procedure to obtain a solution. Various numerical techniques, including scale transformation and regulation method, are proposed. Of those numerical methods, the scale transformation (ST) is the simplest and the most widely used method. However, it presents a high spatial resolution only near the sample surface. Monte Carlo (MC) method is one of the recently proposed ways to solve the equation numerically and has been successfully applied to the analysis of laser intensity modulation method data, which also involves the Fredholm integral equation of the first kind. In this paper we attempt to analyze thermal-pulse data in frequency domain with the MC method and discuss its effectiveness based on some numerical simulations. The simulation results indicate that the electric field profiles can be effectively extracted by the MC method. The computed profiles by the MC method consist well with the supposed distributions in the entire thickness of the sample, while the profiles reconstructed by the ST method fit very well to the supposed one at the vicinity of the target surface and distort sharply along the direction of the thermal pulse propagation in the sample bulk. On the other hand, the oscillations in the computed results by the MC method could deteriorate its accuracy in this study. The influence of noise level on the analysis based on the MC method is also tested by the use of the simulated data. The results show that the computed profiles would become more fluctuant as the noise level increases. This problem can be solved by selecting a larger value of tolerance during the singular value decomposition procedure. Thus, the value of tolerance is considered to be one of the key parameters in this algorithm, which is actually hard to determine. Additionally, the experimental data obtained from a polypropylene film under applied electric field are analyzed to illustrate the feasibility of MC method to be applied to the thermal-pulse experimental data. The results also show that the spatial accuracy by the MC method in the entire sample thickness is higher than by the ST method, which verifies that the MC method is more suitable for detecting the electric field distribution in the deep bulk of the sample. Owing to noise and error, the accuracy of MC calculation depends on the chosen tolerance value, which is now considered to be an obstacle in applying this method to the practical thermal-pulse measurement.

Interleaved quantitative BOLD: Combining extravascular R2ʹ - and intravascular R2-measurements for estimation of deoxygenated blood volume and hemoglobin oxygen saturation