Design And Development Of Visualization Platform Of Brain Magnetic Resonance Image Based On Django Framework

Brain diseases threaten human health,Magnetic resonance imaging can provide clear and intuitive threedimensional anatomical images of the human brain and is an important basis for evaluating normal and abnormal brain pathology.With the continuous development of computer technology and digital image processing technology,medical image visualization technology is constantly updated,the software structure has evolved from the original stand-alone user model to the C/S(Client/Server)model and has evolved into the now prevalent B/S(Browser/ Server)model.With the establishment of a Web-based visualizing platform for stroing brain MR images and for managering a large number of brain magnetic resonance images and patient information,and with the implementation of browser-end loading,analysis,and processing of brain MR images,helps improve information sharing,remote diagnosis and the efficiency of research.The thesis takes advantage of the Django framework's simplicity and suitability for building a databasedriven website,builds a database system of brain MR images,implements DICOM image visualization based on Web browser,designs and develops a platform for storing,querying,visualizing,analyzing and segmentation of brain MR images.The main work of this article is as follows:1.Based on the requirements analysis,determine the technical architecture and design functional modules of the system and establish the corresponding database model.Adopt front-end and back-end development methods.The back end adopts Django + Python + My SQL,and the front-end is based on Node.js + Vue.js + Webpack.It implements the user management module,patient information management module,and back-office management module to study and realize the break-resume transmission of large files.Also,it designs system security for the client,server,and database.2.Outline the DICOM standard and introduce the data structure and encoding of DICOM format files.Using the DWV(DICOM Web Viewer)open source framework and the Canvas tag in the HTML5 standard to achieve the loading of the DCM(DICOM file extension)image on the web browser,and to achieve the analysis of the DCM image.3.On the basis of DCM image loading and analysis,the online operation of the image is completed,including measuring the area of interest,threshold filtering,image sharpening,and edge extraction.Based on the Live Wire algorithm,the interactive segmentation of the image processing interface and the segmentation algorithm based on region growth are implemented to achieve skull segmentation.Through the functional testing of various functional modules,the various functions of the platform are in line with expectations,and truly realize cross-platform,operating system-free porting and remote operation.It provides convenience for researchers' research and doctors' diagnosis,provides quires function for personal information and image of brain patients,and lays a foundation for further research of brain magnetic resonance imaging.