Blood Vessels
How do I map blood vessels in situ?
Micro-CT or LSFM · Labeled vessel maps · Report Panel metrics
Application viewPreclinical neuroscience: map, quantify, and compare on your infrastructure.
Studies now span huge 3D volumes—micro-CT, MRI, light-sheet, and more—yet each data type still needs its own processing stack and viewer. How is your team handling that? How do you process, share, view, and analyze data at scale? How do you compare cohorts to atlases, or bring anatomy, molecular signal, and genomics into one native space for overlay and quantitative readout?
At scale, these data outgrow local storage and computational resources fast.
These data typically require their own software tools.
When you share raw data, analyzed outputs, and how to reproduce the analysis, how do you track versions? Could your collaborators work on the same data and outputs in one shared space?
Many labs mix commercial tools with custom scripts that vary by user and drift when pipelines or people change. How do you keep atlas registration and cohort comparisons consistent and reproducible?
With the NeuroSimplicity Imaging Suite, your teams can bring micro-CT, MRI, light-sheet, and more into one specimen-native workspace on your infrastructure. With a shared working space and reproducible pipelines, your teams can view, edit, and analyze outputs in the same shared environment, with labels registered to atlases in situ, and revisit data as the program and questions grow.
Multi-lab program planningRegister these data to native geometry so overlays and quantitative readouts line up.
Deterministic workflows with traceable regional outputs on your infrastructure.
Inspect, compare, annotate, and share from one shared workspace.
Shared cohort references and cross-site analysis when the question outgrows one group.
See how the Imaging Suite brings anatomy, modalities, cohort metrics, and collaborators into one reproducible environment.