Studies on the characterization of dental whitening process by using both hyperspectral imaging and colorimeter techniques

A beautiful smile is directly related with white teeth. Nowadays oral care has increased and developed processes for beautiful smiles. Dental bleaching is frequently used in odontology, not just for health care also for aesthetic treatment. With the possibility of teeth bleaching, now the importance is in, how white the tooth is? Because color is relate to an individual perception. In order to assets teeth correct color identification has been developed many color guides, models, spaces and analytical methods. Spite all of these useful tools the color interpretation depends on environmental factors, position of the sample in the data acquisition and most importantly the instrument sensitivity. The commons methods have proved to be useful. They are easy to handle, some are portable but they do not have a high sensitivity. The present work is based on the integration of a new analytical technique for color acquisition. High spectral Image (HSI) is able to performed image analysis with high quality and efficiency. HSI is used in many fields and we used it for color image analysis within the bleaching process. The main comparison was done with the HSI and the colorimeter through the processes of two different bleaching protocols. The results showed that HSI has higher sensitivity than the colorimeter. During the analysis the dental surface with the HSI we were able to notice surface changes. These changes were analyzed by roughness studies.

An infrared spectral signature of human lymphocyte subpopulations from peripheral blood.

Metastatic melanomas are frequently refractory to most adjuvant therapies such as chemotherapies and radiotherapies. Recently, immunotherapies have shown good results in the treatment of some metastatic melanomas. Immune cell infiltration in the tumor has been associated with successful immunotherapy. More generally, tumor infiltrating lymphocytes (TILs) in the primary tumor and in metastases of melanoma patients have been demonstrated to correlate positively with favorable clinical outcomes. Altogether, these findings suggest the importance of being able to identify, quantify and characterize immune infiltration at the tumor site for a better diagnostic and treatment choice. In this paper, we used Fourier Transform Infrared (FTIR) imaging to identify and quantify different subpopulations of T cells: the cytotoxic T cells (CD8+), the helper T cells (CD4+) and the regulatory T cells (T reg). As a proof of concept, we investigated pure populations isolated from human peripheral blood from 6 healthy donors. These subpopulations were isolated from blood samples by magnetic labeling and purities were assessed by Fluorescence Activated Cell Sorting (FACS). The results presented here show that Fourier Transform Infrared (FTIR) imaging followed by supervised Partial Least Square Discriminant Analysis (PLS-DA) allows an accurate identification of CD4+ T cells and CD8+ T cells (>86%). We then developed a PLS regression allowing the quantification of T reg in a different mix of immune cells (e.g. Peripheral Blood Mononuclear Cells (PBMCs)). Altogether, these results demonstrate the sensitivity of infrared imaging to detect the low biological variability observed in T cell subpopulations.

Combining T2-preparation with spectral and spatial selectivity for improved coronary MRA

Cardiovascular disease is the leading cause of death worldwide. Within this subset, coronary artery disease (CAD) is the most prevalent. Magnetic resonance angiography (MRA) is an emerging technique that provides a safe, non-invasive way of assessing CAD progression. To generate contrast between tissues, MR images are weighted according to the magnetic properties of those tissues. In cardiac MRI, T2 contrast, which is governed by the rate of transverse signal loss, is often created through the use of a T2-Preparation module. T2-Preparation, or T2-Prep, is a magnetization preparation scheme used to improve blood/myocardium contrast in cardiac MRI. T2-Prep methods generally use a non-selective +90°, 180°, 180°, -90° train of radiofrequency (RF) pulses (or variant thereof), to tip magnetization into the transverse plane, allow it to evolve, and then to restore it to the longitudinal plane. A key feature in this process is the combination of a +90° and -90° RF pulse. By changing either one of these, a mismatch occurs between signal excitation and restoration. This feature can be exploited to provide additional spectral or spatial selectivity. In this work, both of these possibilities are explored. The first - spectral selectivity - has been examined as a method of improving fat saturation in coronary MRA. The second - spatial selectivity - has been examined as a means of reducing imaging time by decreasing the field of view, and as a method of reducing artefacts originating from the tissues surrounding the heart. Two additional applications, parallel imaging and self-navigation, are also presented. This thesis is thus composed of four sections. The first, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", was originally published in the journal Magnetic Resonance in Medicine (MRM) with co-authors Ruud B. van Heeswijk and Matthias Stuber. The second, "Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", again with co-authors Ruud van Heeswijk and Matthias Stuber, was also published in the journal MRM. The third, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA-accelerated image quality in MRA of the right coronary artery", written with co-authors Jerome Yerly and Matthias Stuber, has been submitted to the "Journal of Cardiovascular Magnetic Resonance", and the fourth, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", with co¬authors Jerome Chaptinel, Giulia Ginami, Gabriele Bonanno, Simone Coppo, Ruud van Heeswijk, Davide Piccini, and Matthias Stuber, is undergoing internal review prior to submission to the journal MRM. -- Les maladies cardiovasculaires sont la cause principale de décès dans le monde : parmi celles-ci, les maladies coronariennes sont les plus répandues. L'angiographie par résonance magnétique (ARM) est une technique émergente qui fournit une manière sûre, non invasive d'évaluer la progression de la coronaropathie. Pour obtenir un contraste entre les tissus, les images d'IRM sont pondérées en fonction des propriétés magnétiques de ces tissus. En IRM cardiaque, le contraste en T2, qui est lié à la décroissance du signal transversal, est souvent créé grâce à l'utilisàtion d'un module de préparation T2. La préparation T2, ou T2-Prep, est un système de préparation de l'aimantation qui est utilisé pour améliorer le contraste entre le sang et le myocarde lors d'une IRM cardiaque. Les méthodes de T2-Prep utilisent généralement une série non-sélective d'impulsions de radiofréquence (RF), typiquement [+ 90°, 180°, 180°, -90°] ou une variante, qui bascule l'aimantation dans le plan transversal, lui permet d'évoluer, puis la restaure dans le plan longitudinal. Un élément clé de ce processus est la combinaison des impulsions RF de +90° et -90°. En changeant l'une ou l'autre des impulsions, un décalage se produit entre l'excitation du signal et de la restauration. Cette fonction peut être exploitée pour fournir une sélectivité spectrale ou spatiale. Dans cette thèse, les deux possibilités sont explorées. La première - la sélectivité spectrale - a été examinée comme une méthode d'améliorer la saturation de la graisse dans l'IRM coronarienne. La deuxième - la sélectivité spatiale - a été étudiée comme un moyen de réduire le temps d'imagerie en diminuant le champ de vue, et comme une méthode de réduction des artefacts provenant des tissus entourant le coeur. Deux applications supplémentaires, l'imagerie parallèle et la self-navigation, sont également présentées. Cette thèse est ainsi composée de quatre sections. La première, "A Fat Signal Suppression for Coronary MRA at 3T using a Water-Selective Adiabatic T2-Preparation Technique", a été publiée dans la revue médicale Magnetic Resonance .in Medicine (MRM) avec les co-auteurs Ruud B. van Heeswijk et Matthias Stuber. La deuxième, Combined T2-Preparation and 2D Pencil Beam Inner Volume Selection", encore une fois avec les co-auteurs Ruud van Heeswijk et Matthias Stuber, a également été publiée dans le journal MRM. La troisième, "A cylindrical, inner volume selecting 2D-T2-Prep improves GRAPPA- accelerated image quality in MRA of the right coronary artery", écrite avec les co-auteurs Jérôme Yerly et Matthias Stuber, a été présentée au "Journal of Cardiovascular Magnetic Resonance", et la quatrième, "Combined respiratory self-navigation and 'pencil-beam' 2D-T2 -Prep for free-breathing, whole-heart coronary MRA", avec les co-auteurs Jérôme Chaptinel, Giulia Ginami, Gabriele Bonanno , Simone Coppo, Ruud van Heeswijk, Davide Piccini, et Matthias Stuber, subit un examen interne avant la soumission à la revue MRM.

Imaging polarimetry of the fogbow: polarization characteristics of white rainbows measured in the high Arctic

The knowledge on the optics of fogbows is scarce, and their polarization characteristics have never been measured to our knowledge. To fill this gap we measured the polarization features of 16 fogbows during the Beringia 2005 Arctic polar research expedition by imaging polarimetry in the red, green and blue spectral ranges. We present here the first polarization patterns of the fogbow. In the patterns of the degree of linear polarization p, fogbows and their supernumerary bows are best visible in the red spectral range due to the least dilution of fogbow light by light scattered in air. In the patterns of the angle of polarization α fogbows are practically not discernible because their α-pattern is the same as that of the sky: the direction of polarization is perpendicular to the plane of scattering and is parallel to the arc of the bow, independently of the wavelength. Fogbows and their supernumeraries were best seen in the patterns of the polarized radiance. In these patterns the angular distance δ between the peaks of the primary and the first supernumerary and the angular width σ of the primary bow were determined along different radii from the center of the bow. δ ranged between 6.08° and 13.41° , while σ changed from 5.25° to 19.47° . Certain fogbows were relatively homogeneous, meaning small variations of δ and σ along their bows. Other fogbows were heterogeneous, possessing quite variable δ- and σ-values along their bows. This variability could be a consequence of the characteristics of the high Arctic with open waters within the ice shield resulting in the spatiotemporal change of the droplet size within the fog

Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants

This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.

Influence of data acquisition geometry on soybean spectral response simulated by the prosail model

View angle and directional effects significantly affect reflectance and vegetation indices, especially when daily images collected by large field-of-view (FOV) sensors like the Moderate Resolution Imaging Spectroradiometer (MODIS) are used. In this study, the PROSAIL radiative transfer model was chosen to evaluate the impact of the geometry of data acquisition on soybean reflectance and two vegetation indices (Normalized Difference Vegetation Index - NDVI and Enhanced Vegetation Index -EVI) by varying biochemical and biophysical parameters of the crop. Input values for PROSAIL simulation were based on the literature and were adjusted by the comparison between simulated and real satellite soybean spectra acquired by the MODIS/Terra and hyperspectral Hyperion/Earth Observing-One (EO-1). Results showed that the influence of the view angle and view direction on reflectance was stronger with decreasing leaf area index (LAI) and chlorophyll concentration. Because of the greater dependence on the near-infrared reflectance, the EVI was much more sensitive to viewing geometry than NDVI presenting larger values in the backscattering direction. The contrary was observed for NDVI in the forward scattering direction. In relation to the LAI, NDVI was much more isotropic for closed soybean canopies than for incomplete canopies and a contrary behavior was verified for EVI.

The Effects of Anesthetic Induced Loss of Consciousness on Quantitative Electroen Cephalogram, and Bispectral and Spectral Entropy Indices. Studies on Healthy Male

Changes in the electroencephalography (EEG) signal have been used to study the effects of anesthetic agents on the brain function. Several commercial EEG based anesthesia depth monitors have been developed to measure the level of the hypnotic component of anesthesia. Specific anesthetic related changes can be seen in the EEG, but still it remains difficult to determine whether the subject is consciousness or not during anesthesia. EEG reactivity to external stimuli may be seen in unconsciousness subjects, in anesthesia or even in coma. Changes in regional cerebral blood flow, which can be measured with positron emission tomography (PET), can be used as a surrogate for changes in neuronal activity. The aim of this study was to investigate the effects of dexmedetomidine, propofol, sevoflurane and xenon on the EEG and the behavior of two commercial anesthesia depth monitors, Bispectral Index (BIS) and Entropy. Slowly escalating drug concentrations were used with dexmedetomidine, propofol and sevoflurane. EEG reactivity at clinically determined similar level of consciousness was studied and the performance of BIS and Entropy in differentiating consciousness form unconsciousness was evaluated. Changes in brain activity during emergence from dexmedetomidine and propofol induced unconsciousness were studied using PET imaging. Additionally, the effects of normobaric hyperoxia, induced during denitrogenation prior to xenon anesthesia induction, on the EEG were studied. Dexmedetomidine and propofol caused increases in the low frequency, high amplitude (delta 0.5-4 Hz and theta 4.1-8 Hz) EEG activity during stepwise increased drug concentrations from the awake state to unconsciousness. With sevoflurane, an increase in delta activity was also seen, and an increase in alpha- slow beta (8.1-15 Hz) band power was seen in both propofol and sevoflurane. EEG reactivity to a verbal command in the unconsciousness state was best retained with propofol, and almost disappeared with sevoflurane. The ability of BIS and Entropy to differentiate consciousness from unconsciousness was poor. At the emergence from dexmedetomidine and propofol induced unconsciousness, activation was detected in deep brain structures, but not within the cortex. In xenon anesthesia, EEG band powers increased in delta, theta and alpha (8-12Hz) frequencies. In steady state xenon anesthesia, BIS and Entropy indices were low and these monitors seemed to work well in xenon anesthesia. Normobaric hyperoxia alone did not cause changes in the EEG. All of these results are based on studies in healthy volunteers and their application to clinical practice should be considered carefully.

Spectral clustering independent component analysis for tissue classification from brain MRI

A spectral angle based feature extraction method, Spectral Clustering Independent Component Analysis (SC-ICA), is proposed in this work to improve the brain tissue classification from Magnetic Resonance Images (MRI). SC-ICA provides equal priority to global and local features; thereby it tries to resolve the inefficiency of conventional approaches in abnormal tissue extraction. First, input multispectral MRI is divided into different clusters by a spectral distance based clustering. Then, Independent Component Analysis (ICA) is applied on the clustered data, in conjunction with Support Vector Machines (SVM) for brain tissue analysis. Normal and abnormal datasets, consisting of real and synthetic T1-weighted, T2-weighted and proton density/fluid-attenuated inversion recovery images, were used to evaluate the performance of the new method. Comparative analysis with ICA based SVM and other conventional classifiers established the stability and efficiency of SC-ICA based classification, especially in reproduction of small abnormalities. Clinical abnormal case analysis demonstrated it through the highest Tanimoto Index/accuracy values, 0.75/98.8%, observed against ICA based SVM results, 0.17/96.1%, for reproduced lesions. Experimental results recommend the proposed method as a promising approach in clinical and pathological studies of brain diseases

Sample-induced beam distortions in terahertz time domain spectroscopy and imaging systems

It is demonstrated that distortion of the terahertz beam profile and generation of a cross-polarised component occur when the beam in terahertz time domain spectroscopy and imaging systems interacts with the sample under test. These distortions modify the detected signal, leading to spectral and image artefacts. The degree of distortion depends on the optical design of the system as well as the properties of the sample.

Physical interpretation of the correlation between multi-angle spectral data and canopy height

Recent empirical studies have shown that multi-angle spectral data can be useful for predicting canopy height, but the physical reason for this correlation was not understood. We follow the concept of canopy spectral invariants, specifically escape probability, to gain insight into the observed correlation. Airborne Multi-Angle Imaging Spectrometer (AirMISR) and airborne Laser Vegetation Imaging Sensor (LVIS) data acquired during a NASA Terrestrial Ecology Program aircraft campaign underlie our analysis. Two multivariate linear regression models were developed to estimate LVIS height measures from 28 AirMISR multi-angle spectral reflectances and from the spectrally invariant escape probability at 7 AirMISR view angles. Both models achieved nearly the same accuracy, suggesting that canopy spectral invariant theory can explain the observed correlation. We hypothesize that the escape probability is sensitive to the aspect ratio (crown diameter to crown height). The multi-angle spectral data alone therefore may not provide enough information to retrieve canopy height globally.

Terahertz pulse imaging of stratified architectural materials for cultural heritage studies

Terahertz pulse imaging (TPI) is a novel noncontact, nondestructive technique for the examination of cultural heritage artifacts. It has the advantage of broadband spectral range, time-of-flight depth resolution, and penetration through optically opaque materials. Fiber-coupled, portable, time-domain terahertz systems have enabled this technique to move out of the laboratory and into the field. Much like the rings of a tree, stratified architectural materials give the chronology of their environmental and aesthetic history. This work concentrates on laboratory models of stratified mosaics and fresco paintings, specimens extracted from a neolithic excavation site in Catalhoyuk, Turkey, and specimens measured at the medieval Eglise de Saint Jean-Baptiste in Vif, France. Preparatory spectroscopic studies of various composite materials, including lime, gypsum and clay plasters are presented to enhance the interpretation of results and with the intent to aid future computer simulations of the TPI of stratified architectural material. The breadth of the sample range is a demonstration of the cultural demand and public interest in the life history of buildings. The results are an illustration of the potential role of TPI in providing both a chronological history of buildings and in the visualization of obscured wall paintings and mosaics.

Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3~data

A method has been developed to estimate Aerosol Optical Depth (AOD), Fine Mode Fraction (FMF) and Single Scattering Albedo (SSA) over land surfaces using simulated Sentinel-3 data. The method uses inversion of a coupled surface/atmosphere radiative transfer model, and includes a general physical model of angular surface reflectance. An iterative process is used to determine the optimum value of the aerosol properties providing the best fit of the corrected reflectance values for a number of view angles and wavelengths with those provided by the physical model. A method of estimating AOD using only angular retrieval has previously been demonstrated on data from the ENVISAT and PROBA-1 satellite instruments, and is extended here to the synergistic spectral and angular sampling of Sentinel-3 and the additional aerosol properties. The method is tested using hyperspectral, multi-angle Compact High Resolution Imaging Spectrometer (CHRIS) images. The values obtained from these CHRIS observations are validated using ground based sun-photometer measurements. Results from 22 image sets using the synergistic retrieval and improved aerosol models show an RMSE of 0.06 in AOD, reduced to 0.03 over vegetated targets.

Simple method for sub-diffraction resolution imaging of cellular structures on standard confocal microscopes by three-photon absorption of quantum dots

This study describes a simple technique that improves a recently developed 3D sub-diffraction imaging method based on three-photon absorption of commercially available quantum dots. The method combines imaging of biological samples via tri-exciton generation in quantum dots with deconvolution and spectral multiplexing, resulting in a novel approach for multi-color imaging of even thick biological samples at a 1.4 to 1.9-fold better spatial resolution. This approach is realized on a conventional confocal microscope equipped with standard continuous-wave lasers. We demonstrate the potential of multi-color tri-exciton imaging of quantum dots combined with deconvolution on viral vesicles in lentivirally transduced cells as well as intermediate filaments in three-dimensional clusters of mouse-derived neural stem cells (neurospheres) and dense microtubuli arrays in myotubes formed by stacks of differentiated C2C12 myoblasts.

Synergistic angular and spectral estimation of aerosol properties using CHRIS/PROBA-1 and simulated Sentinel-3 data

We develop a method to derive aerosol properties over land surfaces using combined spectral and angular information, such as available from ESA Sentinel-3 mission, to be launched in 2015. A method of estimating aerosol optical depth (AOD) using only angular retrieval has previously been demonstrated on data from the ENVISAT and PROBA-1 satellite instruments, and is extended here to the synergistic spectral and angular sampling of Sentinel-3. The method aims to improve the estimation of AOD, and to explore the estimation of fine mode fraction (FMF) and single scattering albedo (SSA) over land surfaces by inversion of a coupled surface/atmosphere radiative transfer model. The surface model includes a general physical model of angular and spectral surface reflectance. An iterative process is used to determine the optimum value of the aerosol properties providing the best fit of the corrected reflectance values to the physical model. The method is tested using hyperspectral, multi-angle Compact High Resolution Imaging Spectrometer (CHRIS) images. The values obtained from these CHRIS observations are validated using ground-based sun photometer measurements. Results from 22 image sets using the synergistic retrieval and improved aerosol models show an RMSE of 0.06 in AOD, reduced to 0.03 over vegetated targets.

Modelling spectral reflectance of open cork oak woodland: a simulation analysis of the effects of vegetation structure and background

This study analyses the influence of vegetation structure (i.e. leaf area index and canopy cover) and seasonal background changes on moderate-resolution imaging spectrometer (MODIS)-simulated reflectance data in open woodland. Approximately monthly spectral reflectance and transmittance field measurements (May 2011 to October 2013) of cork oak tree leaves (Quercus suber) and of the herbaceous understorey were recorded in the region of Ribatejo, Portugal. The geometric-optical and radiative transfer (GORT) model was used to simulate MODIS response (red, near-infrared) and to calculate vegetation indices, investigating their response to changes in the structure of the overstorey vegetation and to seasonal changes in the understorey using scenarios corresponding to contrasting phenological status (dry season vs. wet season). The performance of normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and enhanced vegetation index (EVI) is discussed. Results showed that SAVI and EVI were very sensitive to the emergence of background vegetation in the wet season compared to NDVI and that shading effects lead to an opposing trend in the vegetation indices. The information provided by this research can be useful to improve our understanding of the temporal dynamic of vegetation, monitored by vegetation indices.