Texture analysis on two-photon excited microscopic images of human skin hypertrophic scar tissue

According to the pathological characteristics of skin hypertrophic scar tissue, texture features on the edge direction, density distribution and geometric morphology are extracted from two-photon excited microscopic images of scar tissue and used to distinguish the normal tissue from scar tissue. Analysis algorithms of mean-shift are applied to analyze extracted texture features. Finally, a compositive formula is presented for quantitative analysis images. Twenty-five two-photon excited microscopic images originated from human hypertrophic scar tissue are statistically analyzed based on this formula and the inaccuracy rate is 4%. These results indicate that texture features and analytic methods proposed in this paper are effective on distinguishing the normal tissue from scar tissue and accurately fixing on their border.