Medical Image Processor and Repository – MIPAR

Abstract

The recent progress in medical image analysis has given birth to image-guided therapy, virtual reality and augmented reality. These among other innovations have greatly improved healthcare delivery, improved quality of life and also saved lives.. The advances in Internet and network technology have produced web technologies which make it possible to offer platform or software as a service via the web, making it possible for end users to access computer resources or specialized computer tools remotely. However, the high cost of image acquisition, the limited availability of medical image analysts, and the limited collaborative efforts between medical experts and scientists are major challenges for medical image analysis in the developing world. The aim of this project was to develop a medical image e-infrastructure called Medical Image Processor and Analysis (MIPAR) to contain a repository of medical images acquired from Africa and a platform for processing medical images. The backend of MIPAR which is resident on a High-Performance Computing infrastructure was built using FutureGateway, a framework for building science gateway. The image upload and download module was built upon the framework of Open Access Repository with the front end developed using HTML, CSS and BootStrap. JavaScript and JQuery were used for scripting. User's access to the server is controlled with HTTP response and a Client-Server Architecture, while the image processing tools on the server side communicate with PHP using Representational State Architecture (REST) API. MIPAR was tested using brain MRI images. Images were submitted remotely via MIPAR's web interface and kept in the repository. Image processing facility of MIPAR was tested using the brain extraction module, a 3D image of approximately 43MB was successfully brain extracted within 60 s. MIPAR allows users to donate, download and process medical images at no cost. It is our hope that such useful and unique tool will encourage collaboration, improve diagnosis, improve patient management, and promote open science in Africa.