3D Medical Image Modeling utilizing DICOM Data

Medical image visualization has secured an important place in modern diagnostics. The standard format for storage and exchange of such images is DICOM (Digital Imaging and Communications in Medicine). It has nevertheless found extensive application, despite the fact that traditional means of 2D visualization can normally not provide a full understanding of complex anatomical structures. This paper introduces DMIM, a 3D medical image modeling framework that leverages the DICOM structure to enhance medical image visualization. The framework employs high-level Python libraries and integrates MongoDB, a NoSQL database, to efficiently manage large-scale medical datasets. It provides an interactive, web-based 3D visualization platform using WebGL, offering tools for real-time image manipulation such as rotation, zooming, and panning. The DMIM framework presents a scalable and accessible solution, with the potential to significantly impact clinical diagnostics and medical research by enabling intuitive visualization and interpretation of complex medical images.