Analysis software QuantCenter

image analysismanagementreporting

Product overview
QuantCenter is a modular whole-slide image analysis software designed for quantitative histopathology and molecular pathology workflows. It delivers configurable analysis modules, AI- and deep-learning-based segmentation, multi-slide batch processing, integrated visualization, and server-side processing for scalable research and high-throughput studies.

Key modules and functionalities

• HistoQuant: Identifies stained tissue elements using color and intensity features.
• PatternQuant: Trainable pattern recognition for tissue classification and pre-segmentation.
• PatternQuant Plus: Deep-learning-driven extension of PatternQuant for complex tissue segmentation.
• NuclearQuant: Detects and quantifies cell nuclei in IHC-stained samples.
• MembraneQuant: Detects membranes and quantifies membrane-associated IHC signals.
• CellQuant: General-purpose cell detection for various IHC stainings (e.g., Ki67).
• DensitoQuant: Stain-intensity-based IHC quantification tool.
• FISHQuant: Quantifies FISH signals on tissue samples from solid tumors.
• CISHQuant: Quantification for CISH-stained samples.
• DNA Break Quant: Measures double-strand DNA breaks by detecting γH2AX foci in immunofluorescence-stained nuclei.
• ScriptQuant: Executes user-defined image analysis scripts within the QuantCenter environment.
• SimpleSlideInterface: Provides programmatic access to slide metadata and image tiles for custom application development.
• QuantServer: Runs processing jobs and stores results on a dedicated server for centralized, high-performance workflows.
• BatchAnalysis-ProcessingQueue: Background queue for multi-slide batch processing to increase throughput.
• Data Visualization (DVT): Integrated visualization including tables, scatterplots, pie charts, and histograms for result inspection.

Integration and workflow
QuantCenter integrates with slide management systems and supports linkable modules so users can assemble tailored analysis pipelines. Server-side processing and centralized result storage enable scalable deployments and automation of study sample analyses without external tools.

Quantification examples

• Bovine pulmonary artery endothelial cell quantification (HistoQuant).
• Cyprinus carpio epithelium pattern analysis (PatternQuant).
• Elongated villous structures with multilayered nuclei (PatternQuant).
• Estrogen-stained infiltrating ductal carcinoma analysis combining PatternQuant and NuclearQuant.
• Her2-stained breast tissue quantification (DensitoQuant).
• Golgi-stained neuron network detection in rat cortex (HistoQuant).
• Testis tissue analysis including sperm cells (HistoQuant).

Technical features / specifications

• Modular framework allowing selection and combination of specialized quantification modules.
• Customizable AI-driven and deep-learning segmentation for complex tissue tasks.
• Multi-slide batch processing via background processing queue to increase throughput.
• Server-based processing (QuantServer) and centralized storage of results for high-performance workflows.
• Integrated data visualization tools (tables, scatterplots, pie charts, histograms) for inspection and reporting.
• Support for user-defined algorithm integration via ScriptQuant.
• Linkable modules and seamless integration with slide management to automate study analyses.
• Targeted quantification modules for nuclei, membranes, cells, stain intensity, FISH/CISH signals, DNA-damage foci, and pattern-based tissue classification.
• Scalable architecture suitable for research and high-throughput clinical studies.
• Designed for reproducible whole-slide quantification across common whole-slide image formats.