Democratizing data sharing and processing of routine MRI data acquired for neuroimaging research

Neuroimaging research faces five linked barriers: technical complexity, prohibitive costs, lack of transparency, scattered infrastructure, and limited computational resources. Current platforms address these challenges one at a time. As a result, researchers must choose between convenience, transparency, and flexibility. We introduce NeuroStage, a unified, web-based platform that addresses all five barriers together. Technical complexity is removed through a simple interface that requires no programming skills. It supports automatic data upload, anonymisation, organisation of MRI data using the Brain Imaging Data Structure (BIDS) format, and standard preprocessing pipelines. Prohibitive costs are addressed through low-cost open access. The platform can be deployed in the cloud or locally, which also allows processing of protected health information with the same user experience. Lack of transparency is resolved through interactive viewers that let researchers check BIDS classification results and quality control reports before preprocessing begins. This prevents wasted computation on low-quality data. Scattered infrastructure is solved by providing a single platform that handles the entire workflow from scanner to ready-to-use processed and validated data for statistical testing. It also includes a collaborative data repository with secure transfer protocols and metadata-based data sharing. Limited computational resources are addressed by providing server infrastructure through the NeuroStage website. Researchers can run all processing directly from their browser without needing their own computing setup. This is further supported by checkpoint-based fault recovery, which saves completed stages. If processing fails, it can resume from the failure point rather than starting over. Using a multimodal imaging dataset, we show that NeuroStage can detect BIDS misclassifications, perform quality control, and reduce recovery time from preprocessing failures. NeuroStage successfully processed T1-weighted, T2-weighted, diffusion-weighted, resting-state functional, and pseudocontinuous Arterial Spin Labeling MRI using a publicly available toolbox for respective data acquisition without errors. Additionally, NeuroStage provides full quality control reports and detailed processing logs. A demo website showing most of the platform features is available at ( https://neurostagedemo.onrender.com/ , https://github.com/EN4D2-Computational-Lab/NeuroStage-EN4D2.git ). This is currently a proof-of-concept, and continued work towards a public release is ongoing. NeuroStage aims to bring reliable and reproducible neuroimaging analysis to all researchers, including those without access to costly or advanced technology.