Internet-based Medical Data Rendering and Image Enhancement Using Webgl and Apache Server

Abstract

Internet-based medical data visualization has wide applications in distributed medical collaborations and treatment. It can be achieved through volume rendering technique, which is a key method for medical image exploration and has been applied to the clinical medical fields such as disease diagnosis and image-guided interaction.In this project, we implement some medical data processing and optical mapping methods for web-based medical data visualization and image enhancement. The Web Graphics Library (WebGL) is used with JavaScript for rendering 3D graphics in a web browser. WebGL supports GPU based volume rendering which is an efficient tool for visual analysis of medical data, which involves vertex shaders and fragment shaders. The vertex shader provides space coordinates, and the fragment shader provides color.Network-based volume rendering is used to visualize data in a 3D form. An image processing method is implemented to transfer the 3D dataset into multiple slices of 2D image data and WebGL is employed to render 3D medical data in web browsers. Volume rendering is accomplished using the volume ray casting algorithm implemented with WebGL2. We collect new medical data and process them to fit the web-based rendering environment. The submitted work will explain the process of preparing and loading medical data suitable to be rendered. All the visualized data can be enhanced with the developed methods to emphasize the image feature of interest. We also add new control points for optical mapping and rendering medical data in a web browser in real-time. The software platform is running on Apache Web Server for network-based data visualization. The developed image enhancements and property control methods can improve medical data visualization on web browsers, which will be helpful for internet-based medical data analysis and exploration, as well as medical diagnosis and treatment.https://ir.library.illinoisstate.edu/ursit/1000/thumbnail.jp

    Similar works