Frequently Asked Questions

The Imaging Suite runs as an on-premises private cloud deployed directly behind your institution's firewall. Raw imaging data is processed locally on your infrastructure and never leaves your secure environment. You retain full data sovereignty, which simplifies IRB compliance by eliminating third-party data transfers.

After install, core analysis pipelines, atlas libraries, and registration engines can run without internet access. The platform is air-gapped ready for secure government and high-compliance laboratory environments.

Our platform uses deterministic, automated pipelines for feature extraction, atlas registration, and sample-space labeling. Unlike manual tracing or semi-automated tools, the same mathematical rigor is applied to every dataset — delivering auditable reproducibility across operators, sites, and timepoints.

Yes. The pre-processing engine includes automated artifact correction, intensity normalization, and bias field correction. Data that falls below quality assurance thresholds is flagged automatically, so researchers can focus on analysis rather than cleaning data pixel-by-pixel.

Yes. NeuroSimplicity was architected for large data scales in native sample space. Parallelized processing and optimized memory management handle terabyte-scale inputs efficiently, with batch processing across hundreds of samples — removing bottlenecks common in legacy desktop software.

No. The Imaging Suite is Cross-Modal by design. We support the registration and analysis of data from MRI, CT, and Light Sheet Microscopy (LSM) within a unified coordinate framework. This allows for unprecedented Multi-Sample Comparison across different imaging techniques.

You align to the Allen atlas by registering Allen CCFv3 labels to your data in native sample space — mapping the atlas onto your specimen, not warping your specimen into standard space. That sample-space labeling preserves true anatomy (especially with lesions, cranial structures, or cleared-tissue deformation) while delivering Allen region names and quantitative metrics. See our guide to aligning and comparing data to Allen CCFv3.

Standard-space registration forces every volume through the same deformation field. For preclinical specimens — mutant phenotypes, neurovascular cranial imaging, or cleared light-sheet brains — that warping distorts the very structures you are measuring. NeuroSimplicity maps Allen CCFv3 (or custom cohort atlases) to your native sample space so cohort comparison and regional quantification reflect each specimen's real geometry. This is the approach published in Nature and Cell Reports Methods workflows.

Light-sheet analysis in NeuroSimplicity includes automated 3D rendering, segmentation, terabyte-scale batch processing, and cross-modal registration with micro-CT or MRI. When you need Allen atlas comparison, align light-sheet data via sample-space labeling — Allen CCFv3 mapped onto your cleared-tissue volume, not your volume warped into standard space. See how to analyze light-sheet data.

Yes. This is a critical feature for investigating novel phenotypes or developmental stages. The Imaging Suite allows you to generate Custom Population-Specific Atlases directly from your input cohorts (e.g., creating a dedicated "Mutant" vs. "Control" template). This data-driven approach creates a mathematically optimal average of your specific group, ensuring that your registration targets faithfully represent the anatomy of your study population rather than forcing them into an ill-fitting standard space.

Yes. NeuroSimplicity specializes in multi-modal data integration across scales. Our platform can reconstruct 2D serial histology and spatial omics data into coherent 3D volumes. These high-resolution micro-scale datasets are then automatically registered to macro-scale anatomic references, such as micro-CT or light-sheet microscopy. This bridges digital pathology (micro) and anatomic imaging (macro), providing unified molecular and structural context for your research.

Yes. Researchers at NIH and academic institutions have used The Imaging Suite in peer-reviewed discoveries, methods papers, and protocols. Browse our publications →

Yes. Our protocol hub provides interactive, step-by-step workflows derived from peer-reviewed methods papers. For common buyer and PI questions — Allen atlas registration, air-gapped deployment, NIH sole-source, and modality-specific use cases — see the solutions guide. Additional technical documentation is in the sections above.