Imaging & Cell Analysis
FluorocellAI
Automated cell segmentation at research-grade fidelity. The ImageJ workflow your lab already trusts — augmented with transformer-based AI inference that runs at more than 10,000 cells per hour.
Platform Overview
The accuracy you couldn't achieve manually. The workflow you already trust.
FluorocellAI integrates as a native plugin within ImageJ and Fiji, preserving the analytical environment your laboratory has built over years of accumulated macros, scripts, and measurement pipelines. The manual annotation step is replaced with AI inference — everything downstream remains intact.
For high-content screening — 96-well and 384-well plate formats — batch pipelines operate autonomously with automated QC flagging, producing output compatible with KNIME, R, and CellProfiler Analyst without format conversion.
Image Ingestion
TIFF, CZI, LIF, ND2 — direct from acquisition software or OMERO server
Preprocessing
Illumination correction, background subtraction, channel normalisation
AI Inference
Transformer + CNN ensemble — nucleus, boundary, and marker localisation
QC & Export
ROI Manager, Results table, CSV, HDF5 — within the standard ImageJ environment
“Segmentation accuracy indistinguishable from expert manual annotation in our internal benchmarking.”
Dr. M. Kowalski — Senior Research Scientist, Cell Biology
Capabilities
Built for every fluorescence microscopy workflow.
Multi-channel fluorophore analysis
DAPI, GFP, RFP, CY3, CY5, and user-defined custom channel configurations with per-channel threshold tuning and crosstalk correction.
Nucleus & whole-cell segmentation
Simultaneous nucleus detection and whole-cell boundary delineation with configurable expand-from-nucleus distance parameters.
3D volume segmentation
Full volumetric cell segmentation for confocal z-stacks and light-sheet acquisitions with object splitting and merging.
High-content screening
96-well and 384-well plate batch automation with per-well QC metrics, automatic outlier flagging, and plate-level visualisations.
Batch throughput at scale
Process more than 10,000 cells per hour with GPU acceleration. Scales to institutional HPC clusters via distributed batch queues.
Downstream compatibility
Output directly to ImageJ ROI Manager, Results table, CSV, HDF5, and CellProfiler-compatible label maps — no format conversion required.
Use Cases
Who uses FluorocellAI.
Cell Biology Labs
Reduce manual annotation from days to hours for multi-well plate screens. Publish with confidence knowing segmentation accuracy matches peer-reviewed benchmarks.
Core Imaging Facilities
Offer AI-assisted segmentation as a facility service. Batch-process client images without disrupting existing ImageJ/Fiji workflows.
Pharmaceutical CROs
Scale high-content screening throughput without proportionally scaling headcount. Automated QC flags maintain data integrity across large cohorts.
Academic Research Groups
Access institutional-grade segmentation accuracy on an NIH R01 budget. No HPC infrastructure required — runs on standard research workstations.
Begin your FluorocellAI evaluation.
We tailor every evaluation to your imaging modality, cell type, and existing pipeline. Our scientific team guides the process from installation to your first publication-quality output.