Romuald Jolivot

Reconstruction of hyperspectral cutaneous data from an artificial neural network-based multispectral imaging system

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 with bidimensional spatial information. This combined information will hopefully improve diagnosis and follow-up in a range of skin disorders from skin cancer to inflammatory diseases.

Advances in imaging probes and optical microendoscopic imaging techniques for early in vivo cancer assessment.

A new chapter in the history of medical diagnosis happened when the first X-ray technology was invented in the late 1800s. Since then, many non-invasive and minimally invasive imaging techniques have been invented for clinical diagnosis to research in cellular biology, drug discovery, and disease monitoring. These imaging modalities have leveraged the benefits of significant advances in computer, electronics, and information technology and, more recently, targeted molecular imaging. The development of targeted contrast agents such as fluorescent and nanoparticle probes coupled with optical imaging techniques has made it possible to selectively view specific biological events and processes in both in vivo and ex vivo systems with great sensitivity and selectivity. Thus, the combination of targeted molecular imaging probes and optical imaging techniques have become a mainstay in modern medicinal and biological research. Many promising results have demonstrated great potentials to translate to clinical applications. In this review, we describe a discussion of employing imaging probes and optical microendoscopic imaging techniques for cancer diagnosis.

Skin parameter map retrieval from a dedicated multispectral imaging system applied to dermatology/cosmetology

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 reflectance cube is analyzed by an algorithm based on a Kubelka-Munk model combined with evolutionary algorithm. The technique allows quantitative measure of cutaneous tissue and retrieves five skin parameter maps: melanin concentration, epidermis/dermis thickness, haemoglobin concentration, and the oxygenated hemoglobin. The results retrieved on healthy participants by the algorithm are in good accordance with the data from the literature. The usefulness of the developed technique was proved during two experiments: a clinical study based on vitiligo and melasma skin lesions and a skin oxygenation experiment (induced ischemia) with healthy participant where normal tissues are recorded at normal state and when temporary ischemia is induced.

Validation of a 2D multispectral camera: application to dermatology/cosmetology on a population covering five skin phototypes

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 classified based on their skin phototype according to the Fitzpatrick Scale and population covers five of the six types. The acquisition of a participant is performed at three body locations: two skin areas exposed to the sun (hand, face) and one area non exposed to the sun (lower back) and each is reconstructed at 3 different wave ranges. The validation is performed by comparing data acquired from a commercial spectrophotometer with the reconstructed spectrum obtained from averaging the hyperspectral cube. The comparison is calculated between 430 to 740 nm due to the limit of the spectrophotometer used. The results reveal that the multispectral camera is able to reconstruct hyperspectral cube with a goodness of fit coefficient superior to 0,997 for the average of all SPT for each location. The study reveals that the multispectral camera provides accurate reconstruction of hyperspectral cube which can be used for analysis of skin reflectance spectrum.

Analysis of Multispectral Images of Excised Colon Tissue Samples Based on Genetic Algorithms

We present in this paper a method to estimate four significant biological parameters of colon tissue. The interaction of light with colon tissue is modeled by two layers parameterized by biological parameters, which describe optical properties of the colon. This model is reversed using an optimization framework based on genetic algorithms. From a multispectral image of colon, we compute biological parameters of the colon, this noninvasive optical biopsy might lead to better diagnosis of cancer. We present in this paper experimental results analyzing multispectral images of excised colon tissue samples. We analyze the following three categories of colonic tissue: healthy tissue, with a polyp and with cancerous cells.

Unmixing of human skin optical reflectance maps by Non-negative Matrix Factorization algorithm

Abstract 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.

Colour and multispectral imaging for wound healing evaluation in the context of a comparative preclinical study

Accurate wound assessment is a critical task for patient care and health cost reduction at hospital but even still worse in the context of clinical studies in laboratory. This task, completely devoted to nurses, still relies on manual and tedious practices. Wound shape is measured with rules, tracing papers or rarely with alginate castings and serum injection. The wound tissues proportion is also estimated by a qualitative visual assessment based on the red-yellow-black code. Further to our preceding works on wound 3D complete assessment using a simple freehanded digital camera, we explore here the adaptation of this tool to wounds artificially created for experimentation purposes. It results that tissue uniformity and flatness leads to a simplified approach but requires multispectral imaging for enhanced wound delineation. We demonstrate that, in this context, a simple active contour method can successfully replace more complex tools such as SVM supervised classification, as no training step is required and that one shot is enough to deal with perspective projection errors. Moreover, involving all the spectral response of the tissue and not only RGB components provides a higher discrimination for separating healed epithelial tissue from granulation tissue. This research work is part of a comparative preclinical study on healing wounds. It aims to compare the efficiency of specific medical honeys with classical pharmaceuticals for wound care. Results revealed that medical honey competes with more expensive pharmaceuticals.

Source separation on hyperspectral cube applied to dermatology

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 component in the examined skin patch.

Handheld multispectral confocal microscope for cervical cancer diagnosis

We demonstrated a handheld multispectral fluorescence confocal microscope for cervical cancer diagnostic using dual-axis confocal microscope architecture and a microelectromechanical systems scanner. The real time images are acquired with frame rate up to 15 Hz.

Modelling of reflectance spectra of skin phototypes III

In dermatology, study of human skin colour is related to skin phototype (SPT) in which the Fitzpatricks 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 study involving 21 participants with SPT III was performed to study the relationship between reflectance spectra of facultative skin colour and constitutive skin colour obtained using two different instruments namely spectrophometer and multispectral camera. The reflectance spectra is then modelled by different linear regressions over different intervals of wavelength (piecewise linear regressions). Results show that correlation between the modelled reflectance and reflectance obtained from different skin samples using different instruments is very high (R-squared >0.965). For this, it can be inferred that the reflectance model based on piecewise linear regressions is suitable to model SPT III.