0000000000443749
AUTHOR
Romuald Jolivot
showing 11 related works from this author
Quantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative ma…
2012
International audience; This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The analysis is performed on reflectance spectra. The implemented source separation algorithm is based on a multiplicative coefficient upload. The goal is to represent a given spectrum as t…
Source separation on hyperspectral cube applied to dermatology
2010
International audience; This paper proposes a method of quantification of the components underlying the human skin that are supposed to be responsible for the effective reflectance spectrum of the skin over the visible wavelength. The method is based on independent component analysis assuming that the epidermal melanin and the dermal haemoglobin absorbance spectra are independent of each other. The method extracts the source spectra that correspond to the ideal absorbance spectra of melanin and haemoglobin. The noisy melanin spectrum is fixed using a polynomial fit and the quantifications associated with it are reestimated. The results produce feasible quantifications of each source compone…
Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system.
2011
International audience; The development of an integrated MultiSpectral Imaging (MSI) system yielding hyperspectral cubes by means of artificial neural networks is described. The MSI system is based on a CCD camera, a rotating wheel bearing a set of seven interference filters, a light source and a computer. The resulting device has been elaborated for in vivo imaging of skin lesions. It provides multispectral images and is coupled with a software reconstructing hyperspectral cubes from multispectral images. Reconstruction is performed by a neural network-based algorithm using heteroassociative memories. The resulting hyperspectral cube provides skin optical reflectance spectral data combined…
Modelling of Reflectance Spectra of Skin Phototypes III
2011
In dermatology, study of human skin colour is related to skin phototype (SPT) in which the Fitzpatrick's scale is the most used skin photo type classification. Assessment of skin response to UV for various reasons plays an important role in dermatology. This is however not easy to be performed because of two reasons. Firstly, skin areas may have different skin tone resulting in different reflectance spectra and secondly, different modalities may produce different reflectance spectra. We hypothesize that the underlying pattern of reflectance spectra must be similar regardless of the modalities use and the skin areas where it is obtained, for a particular person. An observational clinical stu…
Melanin type and concentration determination using inverse model
2011
Abnormality of melanin production causes skin pigmentation disorders. Currently, assessment of treatment efficacy (under Physician's Global Assessment framework) only refers to visual conditions of skin surface and not the condition of the underlying skin layers and pigments. Albeit researches on models and simulations of light interaction with human skin have been reported, none has been specifically developed for pigmentation analysis of melanin types - eumelanin and pheomelanin. Therefore, our research objectives are to develop image analysis of skin pigmentation for classification and quantification of eumelanin and pheomelanin pigment types in human skin. In this research, the model is…
Determination of reflectance spectra model of skin phototypes V
2012
In dermatology, skin is assessed for its response to UV light and is categorised under the Fitzpatrick skin type (FST). The FST is commonly applied as a predictor of skin cancer. The FST classification however is subjective. To enable an objective assessment, a pattern model of skin colour taken from normal subjects is required. In this paper, a model for skin phototype (SPT) V is developed and presented. We conducted an observational study involving 41 participants with FST V. The study analysed the reflectance spectra of facultative skin and constitutive skin which was captured using spectrophotometer and multispectral camera. Using piecewise linear regression, we modelled the reflectance…
Validation of a 2D multispectral camera: application to dermatology/cosmetology on a population covering five skin phototypes
2011
International audience; This paper presents the validation of a new multispectral camera specifically developed for dermatological application based on healthy participants from five different Skin PhotoTypes (SPT). The multispectral system provides images of the skin reflectance at different spectral bands, coupled with a neural network-based algorithm that reconstructs a hyperspectral cube of cutaneous data from a multispectral image. The flexibility of neural network based algorithm allows reconstruction at different wave ranges. The hyperspectral cube provides both high spectral and spatial information. The study population involves 150 healthy participants. The participants are classif…
Skin Parameter Map Retrieval from a Dedicated Multispectral Imaging System Applied to Dermatology/Cosmetology
2013
International audience; In vivo quantitative assessment of skin lesions is an important step in the evaluation of skin condition. An objective measurement device can help as a valuable tool for skin analysis. We propose an explorative new multispectral camera specifically developed for dermatology/cosmetology applications. The multispectral imaging system provides images of skin reflectance at different wavebands covering visible and near-infrared domain. It is coupled with a neural network-based algorithm for the reconstruction of reflectance cube of cutaneous data. This cube contains only skin optical reflectance spectrum in each pixel of the bidimensional spatial information. The reflect…
Analysis of human skin hyper-spectral images by non-negative matrix factorization
2011
International audience; This article presents the use of Non-negative Matrix Factorization, a blind source separation algorithm, for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The evaluated spectra come from a Hyper-Spectral Image, which is the result of the processing of a Multi-Spectral Image by a neural network-based algorithm. The implemented source separation algorithm is based on a multiplicative coeffi cient upload. The goal is to represent a given spectrum as the weighted sum of two spectral components. The resulting weighted coefficients are used to quantify melanin and hemoglobin content in the given spectra. Results present a …
Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm
2013
International audience; We present in this paper the decomposition of human skin absorption spectra with a Non-negative Matrix Factorization method. In doing so, we are able to quantify the relative proportion of the main chromophores present in the epidermis and the dermis. We present experimental results showing that we obtain a good estimate of melanin and hemoglobin concentrations. Our approach has been validated by analyzing the human skin absorption spectra in areas of healthy skin and areas affected by melasma on eight patients.
Blind source separation of skin chromophores on a hyperspectral cube
2010
International audience; Background/Purpose The ASCLEPIOS system developed by the M2D+ team of the Le2i laboratory (Université de Bourgogne, France) allows determination of a skin reflectance spectrum over the visible wavelength range in each pixel of a 2D image, thereby generating a hyperspectral (3D) cube. Reflectance spectra mainly result from the reflectance of two skin chromophores, epidermal melanin and dermal haemoglobin. A source separation method was applied on the mixed reflectance spectra, resulting in two component spectra for melanin and haemoglobin, respectively. We also obtained through this process quantification of each chromophore in each pixel of a 2D skin image. The accur…