Imaging platforms for detecting and analyzing skin features and Its stability : with applications in skin health and in using the skin as a body-relative position-encoding system

Abstract

Skin imaging is a powerful, noninvasive method used with potential to aid in the diagnosis of various dermatological diseases and assess overall skin health. This thesis discusses imaging platforms that were developed to aid in studying skin features and characteristics at different time and length scales to characterize and monitor skin. Two applications are considered: (1) using natural skin features as a position encoding system and an aid for volume reconstruction of ultrasound imaging and (2) studying natural skin feature evolution or stability over time to aid in assessing skin health. A 5-axis, rigid translational scanning system was developed to capture images at specific locations and to validate skin based body registration algorithms. We show that natural skin features could be used to perform ultrasound based reconstruction accurate to 0.06 mm. A portable, handheld scanning device was designed to study skin characteristics at different time and length scales. With this imaging platform, we analyze skin features at different length scales: [mu]m (for microreliefs), mm (for moles and pores), and cm (for distances between microreliefs and other features). Preliminary algorithms are used to automatically identify microreliefs. Further work in image processing is required to assess skin variation using these images.