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In vitro wound models are useful for research on wound re‐epithelialization. Hyperspectral imaging represents a non‐destructive alternative to histology analysis for detection of re‐epithelialization. This study aims to characterize the main optical behavior of a wound model in order to enable development of detection algorithms. K‐Means clustering and agglomerative analysis were used to group spatial regions based on the spectral behavior, and an inverse photon transport model was used to explain differences in optical properties. Six samples of the wound model were prepared from human tissue and followed over 22 days. Re‐epithelialization occurred at a mean rate of 0.24 mm2/day after day 8 to 10. Suppression of wound spectral features was the main feature characterizing re‐epithelialized and intact tissue. Modeling the photon transport through a diffuse layer placed on top of wound tissue properties reproduced the spectral behavior. The missing top layer represented by wounds is thus optically detectable using hyperspectral imaging This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2020 The Authors. Journal of Biophotonics published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim

Detection of re-epithelialization in wound healing is important, but challenging. Hyperspectral imaging can be used for non-destructive characterization, but efficient techniques are needed to extract and interpret the information. An inverse photon transport model suitable for characterization of re-epithelialization is validated and explored in this study. It exploits scale-invariance to enable fitting of the epidermal skin layer only. Monte Carlo simulations indicate that the fitted layer transmittance and reflectance spectra are unique, and that there exists an infinite number of coupled parameter solutions. The method is used to explain the optical behavior of and detect re-epithelialization in an in vitro wound model. © 2020 Optical Society of America under the terms of the OSA Open Access Publishing Agreement. An OSA-formatted open access journal article PDF may be governed by the OSA Open Access Publishing Agreement signed by the author and any applicable copyright laws. Authors and readers may use, reuse, and build upon the article, or use it for text or data mining without asking prior permission from the publisher or the Author(s), as long as the purpose is non-commercial and appropriate attribution is maintained.

Aim Neonatal jaundice is an important cause of morbidity and mortality, and identifying the condition remains a challenge. This study evaluated a novel method of estimating bilirubin levels from colour‐calibrated smartphone images. Methods A cross‐sectional prospective study was undertaken at two hospitals in Norway from February 2017 to March 2019, with standardised illumination at one hospital and non‐standardised illumination at the other hospital. Healthy term‐born infants with a normal birthweight were recruited up to 15 days of age. The main outcome measures were bilirubin estimates from digital images, plus total bilirubin in serum (TSB) and transcutaneous bilirubin (TcB). Results Bilirubin estimates were performed for 302 newborn infants, and 76 had severe jaundice. The correlation between the smartphone estimates and TSB was measured by Pearson's r and was .84 for the whole sample. The correlation between the image estimates and TcB was 0.81. There were no significant differences between the hospitals. Sensitivity was 100%, and specificity was 69% for identifying severe jaundice of more than 250 µmol/L. Conclusion A smartphone‐based tool that estimated bilirubin levels from digital images identified severe jaundice with high sensitivity and could provide a screening tool for neonatal jaundice. © 2020 The Authors. This is an open access article under the terms of the Creative Commons Attribution‐NonCommercial‐NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.

Hyperspectral imaging is a generic imaging modality allowing high spectral and spatial resolution over a wide wavelength range from the visible to mid-infrared. Short wavelength infrared (SWIR) hyperspectral imaging is currently becoming an important supplement to spectroscopy in optical diagnostics due to the flexibility and adaptability of the technique. However, due to the complexity of hyperspectral data, the analysis requires a well planned approach. In this paper a simple but effective approach combining dimension reduction and unsupervised classification is suggested. Examples of in vivo hyperspectral data in the SWIR spectral range (950-2500 nm) from human skin bruises and porcine skin burns are presented as examples. Data are processed using the minimum noise fraction transform (MNF), and K-means clustering. K-means clustering was found to perform significantly better if applied to MNF transformed data. The classification results agree well with biopsies, spectral data and visual inspection of injuries. It is thus shown that unsupervised clustering can be a preferable technique in cases where it is challenging to use or interpret results from physics based models, or where the ground truth is lacking or not well defined. The presented results confirm that SWIR hyperspectral imaging indeed is a useful tool for optical characterization of tissue. © 2019 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

The spectral and spatial resolution of hyperspectral imaging is useful for investigation of tissue autofluorescence. The low-light, noisy conditions in fluorescence imaging usually necessitates noise removal for extraction of precise spectral signatures and peak shifts. However, noise removal techniques like low-pass filtering or the Maximum Noise Fraction transform might discard information or distort spectral features. In this study, smoothing splines is proposed as an alternative technique to avoid spectral distortion in analysis of hyperspectral fluorescence images in the wavelength range 400-1000 nm. Continuous tuning parameters and use of natural cubic splines makes the method advantageous for unbiased peak extraction. The method was tested on ex vivo images of atherosclerosis lesions and simulations. The method was used to estimate autofluorescence peak shifts, and found to perform well in comparison with MNF. © 2019 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Obtaining a sharp and focused image is essential to fully utilize the advantages of hyperspectral imaging. For line scanning hyperspectral devices, focusing is a challenge in applications where the height and/or position of the imaged object might vary during a scan. Initial focusing is in addition a tedious process that has to be repeated for each sample or measurement. In this paper, a new continuous autofocus tracking system for hyperspectral line-scanning cameras is reported. The presented system is able to automatically and objectively find the correct distance between the camera and the imaged object for proper focus, and retain this focus distance during scan using a laser triangulation system. Concurrent with the focusing, a 3D model of the object is constructed. The system was tested and found to perform well for NIR-SWIR imaging of human hands and test objects with sharp changes in height and contrast. The method is easily adaptable to other spectral ranges and applications, such as industrial conveyor belt applications. The method significantly eases the acquisition of hyperspectral images by ensuring optimal image quality in every scan and eliminating the need for manual refocusing between individual samples. © 2019 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Hyperspectral imaging is a useful tool for characterization of human tissue. However, the vast amount of data created makes it challenging and tedious to manually select spatial regions of interest for further processing. In this study, a random forest-based method was evaluated on basis of its ability to segment human skin regions from the background. The method was compared to the performance of two alternative methods, spectral angle mapper (SAM) and a K-means clustering-based method. The methods were tested on hyperspectral images of ex vivo and in vivo human skin in the wavelength range 400-1000 nm. The random forest approach was found to be robust and perform well regardless of image type. The method is simple to train, and requires minimal parameter tuning for good skin segmentation results. © 2019 Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Diffusion approximation (DA) of the radiative transport equation allows derivation of enclosed solutions for diffuse reflectance from multi-layer scattering structures, such as human skin. Although the DA is known to be inadequate near tissue boundaries and light sources, analytical tractability makes such solutions very attractive for use in noninvasive characterization of biological organs based on measured diffuse reflectance spectra (DRS). For the presented three-layer model of human skin, which enables a good match with DRS in visible spectral range measured with an integrating sphere, the DA solutions systematically overshoot numerically simulated DRS (using Monte Carlo approach) by 1–2 percentage points. However, using the former in inverse analysis of the latter can result in much larger artifacts, most notably overestimations of the melanin and blood contents by up to 15%, which must be considered when analyzing experimental DRS. Despite such systematic errors, the described approach allows simple and robust monitoring of physiological changes in human skin, as demonstrated in tests involving temporary obstruction of blood circulation and seasonal variations due to extensive sun exposure. © 2019 Optical Society of America under the terms of the OSA Open Access Publishing Agreement

The application of hyperspectral imaging in the field of cultural heritage investigation is growing rapidly. In this study, short wavelength infrared hyperspectral imaging (960–2500 nm) has been explored as a potential non-invasive technique for in situ mapping of corrosion products on bronze sculptures. Two corrosion products, brochantite and antlerite, commonly found on the surfaces of outdoor bronze monuments, were considered. Their spatial distribution was investigated on the surface of the bronze sculpture The Man with the Key by Auguste Rodin in Oslo. The results demonstrate that hyperspectral imaging combined with image analysis algorithms can display the distribution of the two corrosion products in different areas (unsheltered and partially sheltered) of the sculpture. © 2018 The Authors.This work is licensed under a Creative Commons BY-NC-ND Licence.

A person's well-being status is reflected by their face through a combination of facial expressions and physical signs. The SEMEOTICONS project translates the semeiotic code of the human face into measurements and computational descriptors that are automatically extracted from images, videos, and three-dimensional scans of the face. SEMEOTICONS developed a multisensory platform in the form of a smart mirror to identify signs related to cardio-metabolic risk. The aim was to enable users to self-monitor their well-being status over time and guide them to improve their lifestyle. Significant scientific and technological challenges have been addressed to build the multisensory mirror, from touchless data acquisition, to real-time processing and integration of multimodal data.

Background Extracorporeal photopheresis that exposes isolated white blood cells to 8-methoxypsoralen (8-MOP) and ultraviolet-A (UV-A) light is used for the management of cutaneous T-cell lymphoma and graft-versus-host disease. 8-MOP binds to DNA of both tumor and normal cells, thus increasing the risk of carcinogenesis of normal cells; and also kills both tumor and normal cells with no selectivity after UV-A irradiation. Hexaminolevulinate (HAL)-induced protoporphyrin-IX is a potent photosensitizer that localizes at membranous structures outside of the nucleus of a cell. HAL-mediated photodynamic therapy selectively destroys activated/transformed lymphocytes and induces systemic anti-tumor immunity. The aim of the present study was to explore the possibility of using HAL instead of 8-MOP to kill cells after UV-A exposure. Methods Human T-cell lymphoma Jurkat and Karpas 299 cell lines were used to evaluate cell photoinactivation after 8-MOP and/or HAL plus UV-A light with cell proliferation and long term survival assays. The mode of cell death was also analyzed by fluorescence microscopy. Results Cell proliferation was decreased by HAL/UV-A, 8-MOP/UV-A or HAL/8-MOP/UV-A. At sufficient doses, the cells were killed by all the regimens; however, the mode of cell death was dependent on the treatment conditions. 8-MOP/UV-A produced apoptotic death exclusively; whereas both apoptosis and necrosis were induced by HAL/UV-A. Conclusion 8-MOP can be replaced by HAL to inactivate the Jurkat and Karpas 299 T-cell lymphoma cells after UV-A irradiation via apoptosis and necrosis. This finding may have an impact on improved efficacy of photopheresis.

Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented. The method makes use of chemometric tools for spectral de-noising (minimum noise fraction (MNF)) and image analysis (multivariate image analysis (MIA) and iterative key set factor analysis (IKSFA)/spectral angle mapper (SAM)) which have given an efficient separation, classification and mapping of colorants from visible-near-infrared (VNIR) hyperspectral images of an ancient illuminated fragment. The identification of colorants was achieved by extracting and interpreting the VNIR spectra as well as by using a portable X-ray fluorescence (XRF) spectrometer.

Hyperspectral imaging, image analysis and diffusion theory were used to visualize skin vasculature and to monitor the development of fresh skin bruises. Bruises were inflicted in a porcine model, and the development of the hemorrhage was monitored using white light hyperspectral imaging (400-1000 nm). Hyperspectral images from human volunteers were also included in the study. Statistical image analysis was used to classify bruised regions and to visualize the skin vasculature. Biopsies were collected from the animals to reveal the true depth of the bruising. A three-layer diffusion model and an analytic hemoglobin transport model were used to model the reflectance spectra from the images. The results show that hyperspectral images contain depth information, and that the approximate depth and extent of bruises can be retrieved using a combination of statistical image analysis and diffusion theory. This technique also shows potential to visualize vascular structures in human skin.

Hyperspectral imagery opens a new perspective for biomedical diagnostics and tissue characterization. High spectral resolution can give insight into optical properties of the skin tissue. However, at the same time the amount of collected data represents a challenge when it comes to decomposition into clusters and extraction of useful diagnostic information. In this study spectral-spatial classification and inverse diffusion modeling were employed to hyperspectral images obtained from a porcine burn model using a hyperspectral push-broom camera. The implemented method takes advantage of spatial and spectral information simultaneously, and provides information about the average optical properties within each cluster. The implemented algorithm allows mapping spectral and spatial heterogeneity of the burn injury as well as dynamic changes of spectral properties within the burn area. The combination of statistical and physics informed tools allowed for initial separation of different burn wounds and further detailed characterization of the injuries in short post-injury time.

Technological solutions regarding automated sorting of food according to their quality parameters are of great interest to food industry. In this regard, automated sorting of fish rest raw materials remains as one of the key challenges for the whitefish industry. Currently, the sorting of roe, milt, and liver in whitefish fisheries is done manually. Automated sorting could enable higher profitability, flexibility in production and increase the potential for high value products from roe, milt and liver that can be used for human consumption. In this study, we investigate and present a solution for classification of Atlantic cod (Gadus morhua) roe, milt and liver using visible and near-infrared hyperspectral imaging. Recognition and classification of roe, milt and liver from fractions is a prerequisite to enabling automated sorting. Hyperspectral images of cod roe, milt and liver samples were acquired in the 400–2500 nm range and specific absorption peaks were characterized. Inter- and intra-variation of the materials were calculated using spectral similarity measure. Classification models operating on one and two optimal spectral bands were developed and compared to the classification model operating on the full VIS/NIR (400–1000 nm) range. Classification sensitivity of 70% and specificity of 94% for one-band model, and 96% and 98% for two-band model (sensitivity and specificity respectively) were achieved. Generated classification maps showed that sufficient discrimination between cod liver, roe and milt can be achieved using two optimal wavelengths. Classification between roe, milt and liver is the first step towards automated sorting. © 2015 Elsevier Ltd. All rights reserved. This is the authors’ accepted and refereed manuscript to the article. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/

This thesis covers a wide field of applications, with an emphasis on applications of reflectance spectroscopy for diagnostic purposes. Reflectance spectroscopy in the visible part of the spectrum has been proved to be a valuable tool in a variety of applications including e. g. port-wine stain diagnostics, diagnostics of liver pathology, neonatal jaundice and age determination of bruises for forensic applications.

Background and Objective Bruises are currently evaluated by visual inspection, and little is known about the first phase after injury. The temporal development of fresh injuries must be accurately described to be able to age bruises in a reliable manner. Color changes in a bruise caused by hemoglobin breakdown products will depend on the severity of the trauma, and thus on the local immune response in the skin. It is therefore important to relate the nature of the impact to the temporal tissue responses. Materials and Methods Controlled injuries were inflicted on anesthetized domestic pigs. Trauma was induced either by a pendulum device, or by paintballs released using pressurized air. The speed of the projectiles was recorded using a high speed camera. Biopsies and reflection spectra (400–850 nm) were collected from normal and bruised skin. The experiments were approved by the national animal research authority. Results The temporal development of the injury was found to depend strongly on the weight and speed of the object. Low speed, blunt objects did not cause persistent skin changes. However, deep muscular bleeding could be found in most cases. High speed, light weight objects caused a rapidly developing bruise. These bruises were fully developed within 15–20 minutes. No deep muscular hemorrhages were observed in those cases. White blood cells (neutrophilic granulocytes) could be found in biopsies from high speed injuries. The amount of white blood cells depended on the time between injury and collection of the biopsies. Conclusion Further investigations utilizing a larger range of object weight and velocities are required to be able to fully classify minor traumatic injuries. Preliminary results indicate that this can be achieved by controlled experiments using a porcine model. Reflectance spectroscopy was found to be a useful tool to study immediate skin reactions to the trauma. Lasers Surg. Med. © 2007 Wiley-Liss, Inc.

Hyperspectral imaging (HSI) is a noncontact and noninvasive optical modality emerging the field of medical research. The goal of this study was to determine the ability of HSI and image segmentation to discriminate burn wounds in a preclinical porcine model. A heated brass rod was used to introduce burn wounds of graded severity in a pig model and a sequence of hyperspectral data was recorded up to 8-h postinjury. The hyperspectral images were processed by an unsupervised spectral–spatial segmentation algorithm. Segmentation was validated using results from histology. The proposed algorithm was compared to K-means segmentation and was found superior. The obtained segmentation maps revealed separated zones within the burn sites, indicating a variation in burn severity. The suggested image-processing scheme allowed mapping dynamic changes of spectral properties within the burn wounds over time. The results of this study indicate that unsupervised spectral–spatial segmentation applied on hyperspectral images can discriminate burn injuries of varying severity. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

The face reveals the healthy status of an individual, through a combination of physical signs and facial expressions. The project SEMEOTICONS is translating the semeiotic code of the human face into computational descriptors and measures, automatically extracted from videos, images, and 3D scans of the face. SEMEOTICONS is developing a multisensory platform, in the form of a smart mirror, looking for signs related to cardio-metabolic risk. The goal is to enable users to self-monitor their well-being status over time and improve their life-style via tailored user guidance. Building the multisensory mirror requires addressing significant scientific and technological challenges, from touch-less data acquisition, to real-time processing and integration of multimodal data.

Background and Objectives Aging of injuries on a victim's body is an important aspect of forensic medicine. Currently, visual assessment and colorimetry based on empirical criteria are the most common techniques for this task, although the results are uncertain. A trauma causing localized vessel damage will rapidly result in a pool of blood in subcutaneous tissues. The color of the bruise is, however, primarily due to hemoglobin transport into dermis and secondarily to its breakdown products. This transport is analyzed in terms of hemoglobin diffusion followed by clearance by macrophage activity, lymphatic flow, and conversion to breakdown products such as bilirubin. The color of a bruise is caused by hemoglobin and hemoglobin breakdown products. The color will change with time, and such color changes can be recorded using reflectance spectroscopy. The aim of this study was to develop a mathematical model to describe blood diffusion within bruised skin, and to use this method to retrieve the age of a bruise from measured skin reflectance. Study Design/Materials and Methods An analytic model was established to describe the development and fading of bruise color. The model, which is based on Darcy's law of convection flow and Fick's law of diffusion, describes the distribution of blood and hemoglobin breakdown products within a hematoma as a function of time after injury. The initial phase after injury is described by a convective extravascular blood flow in subcutaneous tissues, and further development of the bruise is described by diffusion and breakdown of whole erythrocytes and hemoglobin in dermis. Experimental data were used to verify the model. Reflection spectra in the 400–850 nm wavelength range were collected from normal and bruised skin using an integrating sphere setup. The subjects were adult patients admitted to the Department of cardiothoracic surgery, St. Olav's Hospital, Trondheim, Norway. The skin hematomas were caused by external trauma, cardiothoracic examinations, or surgery. Results Preliminary results show that measured and simulated skin reflectance agrees well. The model predicts the age of a hematoma with an accuracy of approximately 1 day. The accuracy of the method depends on precise information of skin thickness in the injured area. The quality of the estimates from the model will thus be enhanced if a reliable measure of skin thickness is collected concurrently with the reflection measurement. Conclusions The time development of a skin hematoma is described with good accuracy by the implemented model. The analytic method provides a theoretical basis for developing an apparatus to determine the age of injuries in forensic medicine. Lasers Surg. Med. 38:277–289, 2006. © 2006 Wiley-Liss, Inc.

Background and Objective Monitoring dynamic changes during laser induced photothermolysis of vascular skin lesions is essential for obtaining an optimal therapeutic result. Rapid photoinduced thermal damage occurs at a threshold temperature of about 70°C. It is therefore, relevant to identify markers to indicate if this threshold temperature has been reached. Methemoglobin, which is formed by a photo-induced oxidation of hemoglobin, indicates that the temperature has reached this threshold value. This study presents a proof of concept of a method for monitoring the in vivo presence of methemoglobin immediately after laser exposure. Study Design/Materials and Methods The present study was designed to investigate the in vivo temperature dependence of hemoglobin absorption in the 450–800 nm spectrum range. In vivo diffuse reflectance measurements of port-wine stain (PWS) and telangiectasia were performed prior to, and immediately after, laser treatment with a pulsed dye laser (PDL) at 585 nm wavelength. Results In vivo measurements following laser treatment of vascular skin lesions showed an immediate increase in the optical absorption of blood. This effect, caused by thermal stress, is a result of an increased dermal blood volume fraction and methemoglobin formation. The effect is light dose dependent, and reflectance spectra revealed methemoglobin formation in patients treated with fluences above 5 J/cm2 at 585 nm wavelength. Conclusions It was proved that methemoglobin can be measured in vivo by reflectance spectroscopy. Measurements of the average methemoglobin concentrations immediately after laser exposure may be a valuable diagnostic tool to verify that the blood temperature has been sufficiently high to induce thermal damage to the vessel wall. Lasers Surg. Med. 34:414–419, 2004. © 2004 Wiley-Liss, Inc.

We apply diffuse reflectance spectroscopy (DRS) and pulsed photothermal radiometry (PPTR) for characterization of the bruise evolution process. While DRS provides information in a wide range of visible wavelengths, the PPTR enables extraction of detailed depth distribution and concentration profiles of selected absorbers (e.g. melanin, hemoglobin). In this study, we simulate experimental DRS spectra and PPTR signals using the Monte Carlo technique and focus on characterization of a suitable fitting approach for their analysis. We find inverse Monte Carlo to be superior to the diffusion approximation approach for the inverse analysis of DRS spectra. The analysis is then augmented with information obtainable by the fitting of the PPTR signal. We show that both techniques can be coupled in a combined fitting approach. The combining of two complementary techniques improves the robustness and accuracy of the inverse analysis, enabling a comprehensive quantitative characterization of the bruise evolution dynamics.

Postprint Imaging of vessel structures can be useful for investigation of endothelial function, angiogenesis and hyper-vascularization. This can be challenging for hyperspectral tissue imaging due to photon scattering and absorption in other parts of the tissue. Real-time processing techniques for enhancement of vessel contrast in hyperspectral tissue images were investigated. Wavelet processing and an inverse diffusion model were employed, and compared to band ratio metrics and statistical methods. A multiscale vesselness filter was applied for further enhancement. The results show that vessel structures in hyperspectral images can be enhanced and characterized using a combination of statistical, numerical and more physics informed models. Copyright 2015 Society of Phot o-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any materi al in this paper for a fee or for commerc ial purposes, or modification of the c ontent of the paper are prohibited

What if you could discover your health status by looking at yourself in the mirror? Since November 2013, the EU FP7 Project SEMEOTICONS is working to make this possible. The Project is building a multi-sensory device, having the form of a conventional mirror, able to read the semeiotic code of the face and detect possible evidence of the onset of cardio-metabolic diseases. The device, called Wize Mirror, integrates unobtrusive imaging sensors used to capture videos, images and 3D scans of the face. These are processed to assess the risk of a cardio-metabolic disease and thereby suggest possible strategies to prevent its onset.

Rheumatoid arthritis (RA) is a disease that frequently leads to joint destruction. It has a high incidence rate worldwide, and the disease significantly reduces patients’ quality of life. Detecting and treating inflammatory arthritis before structural damage to the joint has occurred is known to be essential for preventing patient disability and pain. Existing diagnostic technologies are expensive, time consuming, and require trained personnel to collect and interpret data. Optical techniques might be a fast, noninvasive alternative. Hyperspectral imaging (HSI) is a noncontact optical technique which provides both spectral and spatial information in one measurement. In this study, the feasibility of HSI in arthritis diagnostics was explored by numerical simulations and optimal imaging parameters were identified. Hyperspectral reflectance and transmission images of RA and normal human joint models were simulated using the Monte Carlo method. The spectral range was 600 to 1100 nm. Characteristic spatial patterns for RA joints and two spectral windows with transmission were identified. The study demonstrated that transmittance images of human joints could be used as one parameter for discrimination between arthritic and unaffected joints. The presented work shows that HSI is a promising imaging modality for the diagnostics and follow-up monitoring of arthritis in small joints. © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Hyperspectral imaging provides non-contact, high resolution spectral images which has a substantial diagnostic potential. This can be used for e.g. diagnosis and early detection of arthritis in finger joints. Processing speed is currently a limitation for clinical use of the technique. A real-time system for analysis and visualization using GPU processing and threaded CPU processing is presented. Images showing blood oxygenation, blood volume fraction and vessel enhanced images are among the data calculated in real-time. This study shows the potential of real-time processing in this context. A combination of the processing modules will be used in detection of arthritic finger joints from hyperspectral reflectance and transmittance data. (c) 2015 Society of Photo-Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic electronic or print reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited

Hypercholesterolemia is characterized by high blood levels of cholesterol and is associated with increased risk of atherosclerosis and cardiovascular disease. Xanthelasma is a subcutaneous lesion appearing in the skin around the eyes. Xanthelasma is related to hypercholesterolemia. Identifying micro-xanthelasma can thereforeprovide a mean for early detection of hypercholesterolemia and prevent onset and progress of disease. The goal of this study was to investigate spectral and spatial characteristics of hypercholesterolemia in facial skin. Optical techniques like hyperspectral imaging (HSI) might be a suitable tool for such characterization as it simultaneously provides high resolution spatial and spectral information. In this study a 3D Monte Carlo model of lipid inclusions in human skin was developed to create hyperspectral images in the spectral range 400-1090 nm. Four lesions with diameters 0.12–1.0 mm were simulated for three different skin types. The simulations were analyzed using three algorithms: the Tissue Indices (TI), the two layer Diffusion Approximation (DA), and the Minimum Noise Fraction transform (MNF). The simulated lesions were detected by all methods, but the best performance was obtained by the MNF algorithm. The results were verified using data from 11 volunteers with known cholesterol levels. The face of the volunteers was imaged by a LCTF system (400- 720 nm), and the images were analyzed using the previously mentioned algorithms. The identified features were then compared to the known cholesterol levels of the subjects. Significant correlation was obtained for the MNF algorithm only. This study demonstrates that HSI can be a promising, rapid modality for detection of hypercholesterolemia.

Light propagation in highly scattering biological tissues is often treated in the so-called diffusion approximation (DA). Although the analytical solutions derived within the DA are known to be inaccurate near tissue boundaries and absorbing layers, their use in quantitative analysis of diffuse reflectance spectra (DRS) is quite common. We analyze the artifacts in assessed tissue properties which occur in fitting of numerically simulated DRS with the DA solutions for a three-layer skin model. In addition, we introduce an original procedure which significantly improves the accuracy of such an inverse analysis of DRS. This procedure involves a single comparison run of a Monte Carlo (MC) numerical model, yet avoids the need to implement and run an inverse MC. This approach is tested also in analysis of experimental DRS from human skin.

This is the author’s final, accepted and refereed manuscript to the article. Wound healing is a complex process not fully understood. There is a need of better methods to evaluate the different stages of healing, and optical characterization is a promising tool in this respect. In this study hyperspectral imaging was employed to characterize an in vitro wound model. The wound model was established by first cutting circular patches of human abdominal skin using an 8mm punch biopsy tool, and then creating dermal wounds in the center of the skin patches using a 5mm tool. The wounds were incubated in medium with 10% serum and antibiotics. Hyperspectral images were collected every three days using a push broom hyper spectral camera (Hyspex VNIR1600). The camera had a spectral resolution of 3.7 nm and was fitted with a close up lens giving a FOV of 2.5 cm and a spatial resolution of 29 micrometer. Samples for histology were collected throughout the measurement period, which was 21 days in total. Data were processed in ENVI and Matlab. A successful classification based on hyperspectral imaging of the implemented model is presented. It was not possible to see the healing zone in the in vitro model with the naked eye without dying. The hyperspectral results showed that newly formed epithelium could be imaged without any additional contrast agents or dyes. It was also possible to detect non-viable tissue. In vitro wound models and hyperspectral imaging can thus be employed to gain further insight in the complicated process of healing in different kinds of wounds. © (2014) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only. Copyright 2014. Society of Photo Optical Instrumentation Engineers. One print or electronic copy may be made for personal use only. Systematic reproduction and distribution, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper are prohibited.

Rheumatoid arthritis is a disease that frequently leads to joint destruction. It has high incidence rates worldwide, and the disease significantly reduces patient’s quality of life due to pain, swelling and stiffness of the affected joints. Early diagnosis is necessary to improve course of the disease, therefore sensitive and accurate diagnostic tools are required. Optical imaging techniques have capability for early diagnosis and monitoring of arthritis. As compared to conventional diagnostic techniques optical technique is a noninvasive, noncontact and fast way of collecting diagnostic information. However, a realistic model of light transport in human joints is needed for understanding and developing of such optical diagnostic tools. The aim of this study is to develop a 3D numerical model of light transport in a human finger. The model will guide development of a hyperspectral imaging (HSI) diagnostic modality for arthritis in human fingers. The implemented human finger geometry is based on anatomical data. Optical data of finger tissues are adjusted to represent either an arthritic or an unaffected finger. The geometry and optical data serve as input into a 3D Monte Carlo method, which calculate diffuse reflectance, transmittance and absorbed energy distributions. The parameters of the model are optimized based on HIS-measurements of human fingers. The presented model serves as an important tool for understanding and development of HSI as an arthritis diagnostic modality. Yet, it can be applied to other optical techniques and finger diseases.

Inflammatory arthritic diseases have prevalence between 2 and 3% and may lead to joint destruction and deformation resulting in a loss of function. Patient’s quality of life is often severely affected as the disease attacks hands and finger joints. Pathology involved in arthritis includes angiogenesis, hyper-vascularization, hyper-metabolism and relative hypoxia. We have employed hyperspectral imaging to study the hemodynamics of affected- and non-affected joints and tissue. Two hyperspectral, push-broom cameras were used (VNIR-1600, SWIR-320i, Norsk Elektro Optikk AS, Norway). Optical spectra (400nm – 1700nm) of high spectral resolution were collected from 15 patients with visible symptoms of arthritic rheumatic diseases in at least one joint. The control group consisted of 10 healthy individuals. Concentrations of dominant chromophores were calculated based on analytical calculations of light transport in tissue. Image processing was used to analyze hyperspectral data and retrieve information, e.g. blood concentration and tissue oxygenation maps. The obtained results indicate that hyperspectral imaging can be used to quantify changes within affected joints and surrounding tissue. Further improvement of this method will have positive impact on diagnosis of arthritic joints at an early stage. Moreover it will enable development of fast, noninvasive and noncontact diagnostic tool of arthritic joints

Hyperspectral imaging combines high spectral and spatial resolution in one modality. This imaging technique is a promising tool for objective medical diagnostics. However, to be attractive in a clinical setting, the technique needs to be fast and accurate. Hyperspectral imaging can be used to analyze tissue properties using spectroscopic methods, and is thus useful as a general purpose diagnostic tool. We combine an analytic diffusion model for photon transport with real-time analysis of the hyperspectral images. This is achieved by parallelizing the inverse photon transport model on a graphics processing unit to yield optical parameters from diffuse reflectance spectra. The validity of this approach was verified by Monte Carlo simulations. Hyperspectral images of human skin in the wavelength range 400–1000 nm, with a spectral resolution of 3.6 nm and 1600 pixels across the field of view (Hyspex VNIR-1600), were used to develop the presented approach. The implemented algorithm was found to output optical properties at a speed of 3.5 ms per line of image data. The presented method is thus capable of meeting the defined real-time requirement, which was 30 ms per line of data.The algorithm is a proof of principle, which will be further developed. Estimation of skin optical parameters for real-time hyperspectral imaging applications © The Authors. Published by SPIE under a Creative Commons Attribution 3.0 Unported License. Distribution or reproduction of this work in whole or in part requires full attribution of the original publication, including its DOI.

Hyperspectral images of tissue contain extensive and complex information relevant for clinical applications. In this work, wavelet decomposition is explored for feature extraction from such data. Wavelet methods are simple and computationally effective, and can be implemented in real-time. The aim of this study was to correlate results from wavelet decomposition in the spectral domain with physical parameters (tissue oxygenation, blood and melanin content). Wavelet decomposition was tested on Monte Carlo simulations, measurements of a tissue phantom and hyperspectral data from a human volunteer during an occlusion experiment. Reflectance spectra were decomposed, and the coefficients were correlated to tissue parameters. This approach was used to identify wavelet components that can be utilized to map levels of blood, melanin and oxygen saturation. The results show a significant correlation (p

Measurement of diffuse reflectance spectra (DRS) is a common experimental approach for non-invasive determination of tissue optical properties, as well as objective monitoring of various tissue malformations. Propagation of light in scattering media is often treated in diffusion approximation (DA). The major advantage of this approach is that it leads to enclosed analytical solutions for tissues with layered structure, which includes human skin. Despite the fact that DA solutions were shown to be inaccurate near tissue boundaries, the practicality of this approach makes it quite popular, especially when attempting extraction of specific chromophore concentrations from measured DRS. In this study we analyze the discrepancies between DRS spectra as obtained by using the DA solutions for three-layer skin model and more accurate predictions from Monte Carlo (MC) modeling. Next, we analyze the artifacts which result from the above discrepancies when extracting the parameters of skin structure and composition by fitting the DA solutions to the MC spectra. The reliability and usefulness of such a fit is then tested also on measurements of seasonal changes in otherwise healthy human skin.

Information about the size and depth of a wound and how it is developing is an important prognostic tool in wound diagnostics. In this study a two-camera vision system has been developed to collect optical properties, shape and volume of chronic skin ulcers as tool for diagnostic assistance. This system combines the functionality of 2D imaging spectroscopy and 3D stereo-photogrammetry. A high resolution hyperspectral camera and a monochromatic video frame camera were mounted on the same scanning system. Stereo images were acquired to obtain information about the wound surface geometry. A Digital Surface Model (DSM) of the wound surface was reconstructed by applying stereophotogrammetric methods. The hyperspectral image was co-registered to the monochromatic frame image and the wound border was extracted by applying spectroscopic analysis (e.g. tissue oxygenation, pigmentation, classification). The resulting DSM of the undamaged surroundings of the wound was used to reconstruct the top surface above the wound and thus the wound volume. The analyses can, if desired, be limited to a certain depth of interest like the wound bed or wound border. Simultaneous analysis of the hyperspectral data and the surface model gives a promising, new, non-invasive tool for characterization of chronic wounds. Future work will concentrate on implementation of real time analysis and improvement of the accuracy of the system.

The healing process of chronic wounds is complex, and the complete pathogenesis is not known. Diagnosis is currently based on visual inspection, biopsies and collection of samples from the wound surface. This is often time consuming, expensive and to some extent subjective procedures. Hyperspectral imaging has been shown to be a promising modality for optical diagnostics. The main objective of this study was to identify a suitable technique for reproducible classification of hyperspectral data from a wound and the surrounding tissue. Two statistical classification methods have been tested and compared to the performance of a dermatologist. Hyperspectral images (400-1000 nm) were collected from patients with venous leg ulcers using a pushbroom-scanning camera (VNIR 1600, Norsk Elektro Optikk AS).Wounds were examined regularly over 4 - 6 weeks. The patients were evaluated by a dermatologist at every appointment. One patient has been selected for presentation in this paper (female, age 53 years). The oxygen saturation of the wound area was determined by wavelength ratio metrics. Spectral angle mapping (SAM) and k-means clustering were used for classification. Automatic extraction of endmember spectra was employed to minimize human interaction. A comparison of the methods shows that k-means clustering is the most stable method over time, and shows the best overlap with the dermatologist’s assessment of the wound border. The results are assumed to be affected by the data preprocessing and chosen endmember extraction algorithm. Results indicate that it is possible to develop an automated method for reliable classification of wounds based on hyperspectral data.

Hyperspectral imaging provides means for characterizing large biological samples with microscopic spatial resolution and a narrow spectral sampling interval. However, this approach requires having a measurable light signal in each spectral band. Overcoming the limitations imposed by working with biological samples requires the use of a highly sensitive sensor to detect weak signals. For this study we have built and compared the performance of two imaging spectrometers using optimized for low light environments: an electron-multiplying CCD (EMCCD) and a scientific CMOS (sCMOS). Both systems have been designed to lower the risk of damaging photosensitive samples, delay the bleaching of fluorophores and detect weak fluorescence signals. The cameras work within the VNIR spectral region (400 nm - 900 nm) with a spectral sampling lower than 4 nm. The produced images have scene pixel sizes smaller than 25 μm and a field of view larger than 25 mm. The systems have been tested side to side measuring the diffusion front of a fluorescent tag in samples of porcine skin in challenging light conditions. The study aimed to show the advantages and limitations of each approach. Preliminary results show good performance of the EMCCD for fluorescence applications, whereas more experimental results are needed to be able to conclude on the performance of the sCMOS sensor. However, the sCMOS appears promising for imaging scenes with high dynamics in low light settings.

Optical diagnostics of bruised skin might provide important information for characterization and age determination of such injuries. Hyperspectral imaging is one of the optical techniques that have been employed for bruise characterization. This technique combines high spatial and spectral resolution and makes it possible to study both chromophore signatures and -distributions in an injury. Imaging and spectroscopy in the visible spectral range have resulted in increased knowledge about skin bruises. So far the SWIR region has not been explored for this application. The main objective of the current study was to characterize bruises in the SWIR wavelength range. Hyperspectral images in the SWIR (950-2500nm ) and VNIR (400-850nm) spectral range were collected from 3 adult volunteers with bruises of known age. Data were collected over a period of 8 days. The data were analyzed using spectroscopic techniques and statistical image analysis. Preliminary results from the pilot study indicate that SWIR hyperspectral imaging might be an important supplement to imaging in the visible part of the spectrum. The technique emphasizes local edema and gives a possibility to visualize features that cannot easily be seen in the visible part of the spectrum.

Hyperspectral systems should be specially fitted for bio-applications to achieve optimal results and avoid sample damage. Experiences from developing and using such imaging systems for characterization of bruised skin and fluorescence imaging are described.

Hyperspectral fluorescence imaging is a modality combining high spatial and spectral resolution with increased sensitivity for low photon counts. The main objective of the current study was to investigate if this technique is a suitable tool for characterization of diffusion properties in human skin. This was done by imaging fluorescence from Alexa 488 in ex vivo human skin samples using an sCMOS based hyperspectral camera. Pre-treatment with acetone, DMSO and mechanical micro-needling of the stratum corneum created variation in epidermal permeability between the measured samples. Selected samples were also stained using fluorescence labelled biopolymers. The effect of fluorescence enhancers on transdermal diffusion could be documented from the collected data. Acetone was found to have an enhancing effect on the transport, and the results indicate that the biopolymers might have a similar effect. Hyperspectral fluorescence imaging has thus been proven to be an interesting tool for characterization of fluorophore diffusion in ex vivo skin samples. Further work will include repetition of the measurements in a shorter time scale and mathematical modeling of the diffusion process to determine the diffusivity in skin for the compounds in question.

Post-mortem hypostasis develops due to passive settling of the blood under the effect of gravity after death. Due to consumption of oxygen in the tissues by residual cellular activity after the circulation has stopped, lividity is composed of deoxygenated blood. It has been previously shown that cooling of a body causes lividity to oxygenate, changing from a dark red/blue to a pink/red color, due to hemoglobin’s increased affinity for oxygen at low temperature. This study has confirmed that this occurs by passive diffusion through the skin, but that this can only occur within a limited time frame. The reasons for this process and its potential forensic application require further investigation.