Three Dimensional Computational Analysis of Human Burn Skin

Abstract

More than 50% of skin patients are gone through biopsies for the detection of the disease, however, with current treatment feedback, the effects and the efficacy of the treatment are generally detected several weeks/months after treatment completion. This makes the adjustment of the treatment based on early response, and identification of non-responding patients, nearly impossible. In this thesis a novel method combining optical coherence tomography with a new image processing algorithm is explored as a potential approach to detecting tissue variability. This study involving in-vivo assessment of the near infra-red field attenuation coefficient of normal and burn sub cutaneous skin using swept source optical coherence tomography may indicate that burn skin are more organized by normal one. Here we represents a computational method to detect burn tissues with the goal of automatic surgical margin assessment based on OCT images. Other result demonstrates the feasibility of this computational method in the differential of burn and normal tissues.