Universal in vivo Textural Model for Human Skin based on Optical Coherence Tomograms

TL;DR

This paper develops a universal in vivo skin model using OCT images, analyzing 63 features to objectively differentiate between healthy and diseased skin, including BCC and SCC, aiding clinical diagnosis.

Contribution

It introduces a comprehensive computational model based on optical and textural features from OCT images for skin disease diagnosis, addressing variability across body sites.

Findings

Successfully differentiates BCC and SCC from healthy tissue

Provides objective support for clinical decision-making

Demonstrates robustness across different skin sites

Abstract

Currently, diagnosis of skin diseases is based primarily on visual pattern recognition skills and expertise of the physician observing the lesion. Even though dermatologists are trained to recognize patterns of morphology, it is still a subjective visual assessment. Tools for automated pattern recognition can provide objective information to support clinical decision-making. Noninvasive skin imaging techniques provide complementary information to the clinician. In recent years, optical coherence tomography has become a powerful skin imaging technique. According to specific functional needs, skin architecture varies across different parts of the body, as do the textural characteristics in OCT images. There is, therefore, a critical need to systematically analyze OCT images from different body sites, to identify their significant qualitative and quantitative differences. Sixty-three optical and textural features extracted from OCT images of healthy and diseased skin are analyzed and in conjunction with decision-theoretic approaches used to create computational models of the diseases. We demonstrate that these models provide objective information to the clinician to assist in the diagnosis of abnormalities of cutaneous microstructure, and hence, aid in the determination of treatment. Specifically, we demonstrate the performance of this methodology on differentiating basal cell carcinoma (BCC) and squamous cell carcinoma (SCC) from healthy tissue.