Morphometric analysis of dermal collagen can provide quantitative support to dermatologic research. The authors of this article disclose a technique of digital image analysis which allows the identification of microscopic structures by color cluster segmentation regarding the estimate intensity and density of dermal collagen fibers. Keywords: Image cytometry; Cluster analysis; Collagen Resumo: Análise morfométrica do colágeno dérmico pode fornecer subsídio quantitativo para a pesquisa em dermatologia. Os autores demonstram uma técnica de análise de imagem digital que permite a identificação de estruturas microscópicas, a partir da segmentação por conglomerados (clusters), de cor aplicada à estimativa da intensidade e densidade das fibras colágenas da derme. Palavras-chave: Análise por conglomerados; Citometria por imagem, Colágeno Histological cuts of computational morphometry represent an important tool in biomedical research, integrating the objectiveness of the measurements, high level of reproducibility, low cost, independence of human subjectiveness and partiality, possibility of quantitative analysis of the variables and a great number of publications available.
2The estimate epidermic thickness, hyperkeratosis, parakeratosis, melanic pigmentation, depth of tumours, inflammatory infiltrate, volume of the glands, immunohistochemical marks, heterogeneity of chromatin, dermic elastosis and collagen alterations are some direct applications of morphometry to microscopic skin cuts. [3][4][5] In spite of the availability of specific commercial systems of morphometry, structures can be quantified using a simple microscope of light, attached to digital cameras and analyzed by free softwares such as the ImageJ, making it possible to promote the diffusion of quantitative research in dermatology. 6,7 In this study we present a strategy to estimate the density and intensity of collagenous fibers on the skin, which is an important variable in studies about ageing, genetic syndromes, fibromatosis and colagen diseases, besides therapeutic comparissons.There are various systems of color to operate morphometry, outstanding the HSB, the LAB, the XYZ and the RGB, the most commonly used. This means that the pixels of an image can be interpreted as shinning points with intensities of color that can be decomposed into channels such as: red (R), green (G) and blue (B). If each pixel projects its composition of color into a tridimensional orthogonal system RXGXB, it is possible to identify in this virtual space groups of points which are related to the shades of color of the image. Cluster analysis is a computational tool that can identify such groupings of points and substitute them by its median value (centroid), creat-