Quantification of Blood Flow Velocity in the Human Conjunctival Microvessels Using Deep Learning-Based Stabilization Algorithm.

The quantification of blood flow velocity in the human conjunctiva is clinically essential for assessing microvascular hemodynamics. Since the conjunctival microvessel is imaged in several seconds, eye motion during image acquisition causes motion artifacts limiting the accuracy of image segmentation performance and measurement of the blood flow velocity. In this paper, we introduce a novel customized optical imaging system for human conjunctiva with deep learning-based segmentation and motion correction.

Correlation between light absorbance and skin color using fabricated skin phantoms with different colors.

The objective of this study is to investigate the need for detailed classification of skin colors through the quantification of skin color and light absorbance differences. Skin color is one of the most important factors in dermatological laser treatments. Dermatological laser treatments are currently performed based on the experience and judgment of the doctor with the Fitzpatrick scale.

Observations of in vivo laser tissue ablation in animal models with different chromophores on the skin and modulating duration per laser exposure.

Characteristics such as skin tone and pigmentation color vary among patients, but most researches on laser irradiation in laser ablation have revolved around minimizing damage to reduce pain. Chromophores are the most important factors in photon energy absorption, a key principle of laser ablation. We investigated the influences on ablation depth by different chromophores on the target and modulating duration per laser exposure using an Nd:YVO4 nanosecond 532-nm laser.