Glia, Quantified
Microglia ramification, astrocyte territory, oligodendrocyte process complexity — measured at cohort scale with batch reproducibility. Activation states classified per cell, longitudinal change tracked across timepoints.
Four Metrics. Whole-brain Reach.
The morphology shifts before the transcriptome does. Quantify the change before you call it gliosis.
Ramification Index
Per-cell process complexity from Iba1+ skeletons — total branch length, end-point count, branch order, soma area. Discriminate ramified, hyper-ramified, and amoeboid microglia at scale.
RI = Σ branch_len / soma_areaTerritory Volume
Astrocyte domain volume from 3D convex hull plus skeletal extent. Captures process span, primary process count, and neighbour-domain overlap — the readout that moves first under reactive gliosis.
V = ConvexHull(skeleton)Activation Classification
Per-cell morphological state assignment — homeostatic, reactive, primed, hyper-ramified. Threshold-based or trained-classifier modes with QC overlays so you can see why each cell got its label.
class = f(RI, soma, sphericity)Batch Comparison
Cohort-scale processing across full sections or atlas regions. Group-level statistics by treatment, genotype, brain area, and timepoint — without re-running ImageJ macros for each animal.
cohort × region × timepointMarkers by Cell Type
Single-marker workflows or co-stained multi-channel — the same engine reads both. Phenotype across markers per cell.
| Cell Type | Common Markers | Morphometry Output |
|---|---|---|
| Microglia | Iba1CX3CR1-GFPTMEM119P2RY12 | Ramification index, branch count, end-point density, soma area, sphericity, activation class. |
| Astrocytes | GFAPS100BALDH1L1AQP4 | Territory volume, process span, primary process count, neighbour overlap, reactive score. |
| Oligodendrocytes | MBPOlig2CC1 (APC)MAG | Process complexity, internode length, sheath count (with MBP), maturation stage. |
Multi-marker co-staining supported across all three cell types.
Activation, Per Cell
Each cell carries its own morphology vector and class label, with QC overlays showing why. Longitudinal change tracked across timepoints in the same region.
From Z-Stack to Cohort Statistics
Four steps. One pipeline. No ImageJ macro per animal.
Built on the Methods That Work
The morphometric definitions the field already trusts — codified, batched, reproducible.
Glia, Quantified at Scale
Morphology shifts before transcripts do. Bring your Z-stacks; we will return per-cell metrics, activation classes, and cohort statistics ready for the next figure.
