Core facilities · Scale

What do imaging core facilities need for terabyte-scale multi-modal throughput?

If you direct or staff a shared preclinical imaging core, you need to serve multiple PIs and modalities without single-seat desktop bottlenecks, process terabyte cohorts reliably, deliver reproducible audit-ready results, and give labs a path to analyze and share their data without depending entirely on core queue time.

What researchers typically do

Core facilities typically provide access to Imaris, Fiji, Amira, QuPath, or vendor software on dedicated workstations in the core. Each lab project generates different data types requiring different analyses and producing different file formats. Operators trace structures manually or run semi-automated scripts that vary by user, and terabyte cleared-tissue light-sheet or serial whole-slide stacks exceed what those machines handle in parallel. When several labs need the same seat, work backs up. When pipelines differ by operator, results are difficult to reproduce or defend in grant review. Because the software sits on core workstations, investigators often cannot bring data back to their own lab to analyze, build figures, discuss with their group, or reopen their volumes independently. Institutions and cores favor this model because it centralizes licenses and expertise, and that centralization makes sense. It also leaves labs waiting on core queue time and dependent on file formats they cannot open on their own machines. Institutions can still centralize resources around a core, improve collaborative grant competitiveness, increase ROI, and standardize processing while letting labs open and use their own data through core sublicensing of standard software or a shared platform on a per-project basis.

Centralize the core, open access for labs

The NeuroSimplicity Imaging Suite is built for that model. You can run server-side terabyte batch processing and concurrent user licenses on institutional infrastructure so the core standardizes deterministic pipelines while PI labs analyze, review, and share results from the same platform. You can apply automated feature extraction and atlas registration to the sample across operators and batches, with QA flagging sub-threshold data quality. You can support grant review and multi-site harmonization with identical processing logic and auditable history. Portal ROI tools help core directors model per-project sublicensing and institutional investment cases.

What the platform enables

  • Dedicated NeuroSimplicity workstation per licensed user, connected to the institutional private cloud
  • Concurrent user licenses for multi-PI shared cores
  • Deterministic pipelines with automated QA across operators and batches
  • Per-project sublicensing so PI labs can access and analyze their data through the core
  • Multi-PI cohort management across micro-CT, light-sheet, whole-slide, and spatial omics
  • ROI modeling for core sublicensing (portal tools)

More detail

Deterministic pipelines replace operator-dependent manual tracing that drives inter-observer variability across core users.

Each licensed user gets a dedicated NeuroSimplicity workstation to interact with the core's institutional private cloud deployment.

Per-project sublicensing through the core lets PI labs open, analyze, and share their data without relying solely on dedicated core workstations.

ROI modeling tools in the portal help core directors build sublicensing and institutional investment cases.

Next steps

On-premises deploymentPrivate cloud on institutional infrastructure vs. shared desktop workstationsConfigure licensingPlan concurrent licenses and module capacity for core throughputCore ROI brief generatorModel sublicensing revenue and institutional investment for core directorsAutomation & reproducibility FAQDeterministic pipelines, QA, and audit-ready processing for shared cores
Core Facility Neuroimaging at Scale | NeuroSimplicity