Adding functionalities to medical imaging visualizations

MedEye3D.jl aims to enhance medical imaging visualization within the Julia language ecosystem. The current proposal addresses the need for improved functionality in windowing, support for the display of super voxels, faster load times, and robust viewing of multiple images. By leveraging Rocket.jl and ModernGL.jl, the proposal plans to implement features like enhanced windowing for MRI and PET data, support for the display of super voxels, and high-level functions for improved user experience. The project aims to streamline visualization processes and provide essential tools for 3D medical imaging workflows. The main deliverables include: Supporting simultaneous visualization of multiple registered medical images, with linked scrolling, cursor highlighting, and connecting lines between annotated points across images. Implementing automatic windowing and colormaps for common MRI and PET imaging modalities to provide consistent visualizations mimicking other medical imaging software. Adding support for visualizing supervoxel segmentations with boundary detection using techniques like the Sobel filter. Improving startup time by precompiling critical components of the package. Implementing high-level functions to simplify basic usage by abstracting away low-level details of image loading, rendering, and visualization. By enhancing MedEye3D.jl with these features, the project aims to provide a more comprehensive and user-friendly tool for 3D medical image visualization and analysis within the Julia ecosystem. The improvements will facilitate better integration into medical imaging workflows and enable more efficient exploration and interpretation of data across different modalities.