Real-time skin chromophore estimation from hyperspectral images using a neural network.

BACKGROUND: Hyperspectral imaging for in vivo human skin study has shown great potential by providing non-invasive measurement from which information usually invisible to the human eye can be revealed. In particular, maps of skin parameters including oxygen rate, blood volume fraction, and melanin concentration can be estimated from a hyperspectral image by using an optical model and an optimization algorithm. These applications, relying on hyperspectral images acquired with a high-resolution camera especially dedicated to skin measurement, have yielded promising results. However, the data analysis process is relatively expensive in terms of computation cost, with calculation of full-face skin property maps requiring up to 5 hours for 3-megapixels hyperspectral images. Such a computation time prevents punctual previewing and quality assessment of the maps immediately after acquisition. METHODS: To address this issue, we have implemented a neural network that models the optimization-based analysis algorithm. This neural network has been trained on a set of hyperspectral images, acquired from 204 patients and their corresponding skin parameter maps, which were calculated by optimization. RESULTS: The neural network is able to generate skin parameter maps that are visually very faithful to the reference maps much more quickly than the optimization-based algorithm, with computation times as short as 2 seconds for a 3-megapixel image representing a full face and 0.5 seconds for a 1-megapixel image representing a smaller area of skin. The average deviation calculated on selected areas shows the network's promising generalization ability, even on wide-field full-face images. CONCLUSION: Currently, the network is adequate for preview purposes, providing relatively accurate results in a few seconds.

Appearance of aging signs in differently pigmented facial skin by a novel imaging system.

BACKGROUND: Facial wrinkles, pores, and uneven skin tone are major beauty concerns. There is differential manifestation of aging signs in different ethnic groups. In this regard, studies on Black Africans from the African continent are scarce. OBJECTIVE: To investigate facial wrinkles, pores, and skin tone in Black African women from Mauritius Island and elucidate the differences to Caucasian women from France. METHODS: Facial images were taken using the imaging system ColorFace® . Wrinkles and pores were measured by their length, depth, surface, volume, and number; for skin tone, we measured L*a*b* and calculated ITA, IWANewtone , and color homogeneity. RESULTS: We found good correlations of wrinkle and pore scores with expert ranking done on ColorFace® images for Caucasians (Spearman's rho = 0.78 and 0.72) and Black Africans (Spearman's rho = 0.86 and 0.65). Caucasians showed more advanced facial signs of aging than Black Africans. Exceptions were vertical lines on upper lip and the depth of pores which were greatest for the Black African subjects. Black Africans had higher heterogeneity scores indicative for uneven skin tone. Luminance (L*) was significantly higher in Caucasians but a* and b* values were significantly higher in the Black African subjects. ITA and IWANewtone were significantly higher for Caucasians. CONCLUSIONS: The high correlation between expert ranking and wrinkle and pore measurements prove ColorFace® a valid imaging system to study skin aging. Our results show that Africans from the African continent show delayed signs of aging compared to Caucasians. Some exceptions suggest that ethnic differences in facial aging are a complex phenomenon.

Three-dimensional maps of human skin properties on full face with shadows using 3-D hyperspectral imaging.

Hyperspectral imaging has shown great potential for optical skin analysis by providing noninvasive, pixel-by-pixel surface measurements from which, applying an optical model, information such as melanin concentration and total blood volume fraction can be mapped. Such applications have been successfully performed on small flat skin areas, but existing methods are not suited to large areas such as an organ or a face, due to the difficulty of ensuring homogeneous illumination on complex three-dimensional (3-D) objects, which leads to errors in the maps. We investigate two methods to account for these irradiance variations on a face. The first one relies on a radiometric correction of the irradiance, using 3-D information on the face's shape acquired by combining the hyperspectral camera with a 3-D scanner; the second relies on an optimization metric used in the map computation, which is invariant to irradiance. We discuss the advantages and drawbacks of the two methods, after having presented in detail the whole acquisition setup, which has been designed to provide high-resolution images with a short acquisition time, as required for live surface measurements of complex 3-D objects such as the face.