3D
spheroid-tissue analysis
Micro Solutions / Life Science
CellPathfinder High Content Analysis Software
From Cell Imaging to Quantitative Outcome: Analysis, Machinery and Deep Learning
Product overview
- CellPathfinder
- Yokogawa
- Japan
- CellVoyager
- CellPathfinder
From Cell Imaging to Quantitative Outcome: Analysis, Machinery and Deep Learning
With ready-made protocols and 3D visualization for CellVoyager and Single Cellome systems
CellPathfinder is a Yokogawa software environment for converting large arrays of HCA images into reproducible quantitative results.
Ready-made protocols and visual workflows simplify cell segmentation, measurement and comparison by well and time point, and support 3D analysis of Z stacks, tracking, graphs, gated, calculations of Z factor and EC50/IC50, as well as Machine Learning and Deep Learning for complex phenotypes and label-free tasks.
CellPathfinder works with CQ1 and CellVoyager systems. The dedicated workstation configuration in the official newsletter includes 128 GB of RAM, 1 TB system disk, 4 TB storage, Windows 11 IoT Enterprise 64-bit, NVIDIA RTX A400 or RTX 4000 Ada GPU and two 2560×1440 monitors; the composition depends on the delivery version.
Key figures
ML/DL
machine- and deep-learning
128GB
RAM of the senior configuration
4
compatible Yokogawa platforms
Applications
- High-content screening
- 3D analysis of spheroids and tissues
- Cell classification
- Label-free analysis
- Time-lapse experiments
- Immunology
Models and configurations
- CellPathfinder
Product details
Visual interface analysis
triggering
3D visualization of results
voluminous
Analysis opportunities
- Basic functions: counting cells, cell cycle, morphology of colonies and spheroids, tracking calcium signals and neurites
- 3D, tiles and texture analysis with graphs: bar, line, pie, scatter, heatmap, histogram
- EC50/IC50 and Z' factor for quantifying experiments
Machine and deep learning
- Optional segmentation and gated modules based on Machine Learning and Deep Learning
- Label-free analysis of light-field images without staining cells
- Tracking objects and daughter cells after division to analyze cell lines
Compatibility and output
- It works with CellVoyager CV8000, CQ1, CQ3000 and Single Cellome SS2000.
- Export of numerical data to CSV, images to PNG/JPEG/TIFF, video to WMV and MPEG4
- Ready-made analytical protocols for a quick start without expertise in image analysis
Modules and functions
| Basic functions | 3D analysis, tiles and texture analysis, graphs, 3D Viewer, EC50/IC50, Z' factor |
|---|---|
| Optional functions | Tracking of area over time and objects, gateway (quadrotree, rectangular, polygonal, linear), CE Bright Field, Machine Learning and Deep Learning (segmentation, cell counting, gate, EC50/IC50) |
| Analysis modes | Single, package, automated |
Compatibility and data
| Compatible equipment | CellVoyager CV8000, CQ1, CQ3000, Single Cellome SS2000 |
|---|---|
| Formats of withdrawal | numerical data – CSV; images – PNG/JPEG/TIFF; video – WMV, MPEG4 |
Requirements for the workstation (assembly by the customer)
| Min. configuration - Basic Pack | Intel Xeon CPU (PassMark ≥7389) or EQ; NVIDIA Quadro GPU (PassMark ≥2225) or EQ; 32 GB RAM; 1920×1080 monitor; network 1 node |
|---|---|
| Configuration with Machine Learning | Intel Xeon CPU (PassMark ≥8492) or faster; NVIDIA Quadro GPU (PassMark ≥5653) or faster; 64 GB RAM; two 1920×1200 or 2560×1440 monitors; 10GbE network |
| Configuration with Deep Learning | GPU Quadro RTX5000, RTX A4500 or RTX 4000 Ada; 128 GB RAM; Storage: 1st drive from 1 TB, 2nd from 4 TB; Windows 11 Pro 25H2, 64-bit |
Yokogawa Standard Workstation (Complete Delivery)
| Processor and memory | Intel Xeon, 128GB of RAM; drives: system 1TB, 4TB data |
|---|---|
| Video card | NVIDIA RTX A400 (standard) or RTX 4000 Ada (high performance option) |
| OS | Windows 11 IoT Enterprise, 64-bit |
| Monitor | two 27" monitors, resolution 2560×1440 |
| Body and mass | 176.5×452.1×417.9 mm, 17 kg |
Optional modules
Machine Learning
Segmentation and gated on classical algorithms (requires Gate option)
Deep Learning
Segmentation, cell counting, gated and EC50/IC50 on neural networks (requires Gate option)
CE Bright Field
Reconstruction of light-field image in the analysis process
Workstation with GPU increased performance
NVIDIA RTX 4000 Ada instead of RTX A400
Related equipment types
- High-Content Analysis Systems CellVoyager
- Inverted microscopes
- Workstations for image analysis
- Monitors for data visualization
Related products
- Yokogawa CV8000 — High-Content Analysis Systems CellVoyager
- Ningbo Sunny Instruments EX30 — Inverted microscopes
- Berthold NightSHADE LB 985 — Monitors for data visualization
Classification
- Immunology
- High-content analysis systems
- Microscopy and imaging systems
- Image analysis and morphometry
- CellPathfinder