Psoriasis is a common skin disease affecting an average of 1.5\% of men and women worldwide. One method for assessing psoriasis's severity is the so-called PASI (Psoriasis Area Severity Index) score. The PASI score calculation consists of four parameters: redness, thickness, scaling, and area. These four parameters are evaluated for each of the anatomic regions. Currently, the PASI score assessment is done manually by a medical practitioner.
This project aims to improve a prototype 3D skin surface reconstruction camera system that can be used to evaluate PASI scores in an automated and structured manner. This will be accomplished by introducing inertial sensor fusion in combination with the current SLAM algorithm to improve the accuracy and robustness of the localization and mapping of the camera system and skin surface. A synchronization system will be designed to synchronize image acquisition, inertial sensor data, and light pattern projection. Further, the system architecture and hardware will be redesigned to increase throughput times and overall stability.
The design of a prototype handheld 3D surface reconstruction setup for monitoring skin diseases
Finished: 2021-07-09
MSc assignment