Patient-Centered Monitoring and Image Processing on Smartphone

Abstract

Surgery Site Infection (SSI) is an infection that occurs after surgery in the part of the body where the surgery took place. It typically occurs within 30 days after the surgery (and discharge from the hospital). With rapid advance of sensing and mobile technologies, today more methods may be used to control the risk of SSI. In particular, mobile phones can be one of the most convenient and effective tools for monitoring SSI prognosis. The purpose of this research was to develop an algorithm for deforming the surgery site image to help monitor SSI risk and implement the algorithm on IOS devices. With proper deformation, the surgery site image can be readily analyzed using mobile phones with limited computational power. Our work focused on the so-called thin-plate spline interpolation, which is a two-dimensional extension of the cubic spline in one dimension. Compared with other spatial interpolation functions, the thin-plate spline is smooth and numerically stable. We implemented a thin-plate spline based deformation algorithm using both Matlab (for PCs) and Object-Oriented C (for IOS devices) programming languages, and showed promising deformation results for surgery site images.