> For the complete documentation index, see [llms.txt](https://docs.owkin.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.owkin.com/connect-and-integrate/pathology-explorer-mcp-ai-powered-tissue-analysis.md).

# Pathology Explorer MCP : AI-Powered Tissue Analysis

Pathology Explorer is an advanced AI tool that transforms standard hematoxylin and eosin (H\&E) histology slides into detailed, queryable insights. By analyzing the complex spatial organization of the tumor microenvironment (TME), it enables researchers to uncover patterns that traditional histology analysis often misses—patterns that are critical for predicting treatment response and understanding disease progression.

### Key Capabilities

* **Comprehensive Cell Segmentation and Classification:** Trained on over 200,000 expert annotations, Pathology Explorer automatically segments and classifies all cells within a tissue sample in minutes, providing unprecedented granularity in tissue analysis.
* **Actionable Biomarker Discovery:** Transform raw histology data into interpretable, clinically relevant biomarkers that can inform research decisions and therapeutic strategies.
* **State-of-the-Art AI Architecture:** Powered by Owkin's advanced deep learning models, rigorously benchmarked against 6+ leading encoders and best-in-class architectures to ensure accuracy and reliability.
* **Large-Scale Database Integration:** Seamlessly analyze H\&E slides from major databases including The Cancer Genome Atlas (TCGA), enabling large-scale retrospective and prospective studies.

### Applications

Pathology Explorer empowers researchers and clinicians to:

* Quantify spatial relationships within the tumor microenvironment
* Identify predictive biomarkers for treatment response
* Accelerate histopathology research with automated, reproducible analysis
* Generate hypotheses about disease mechanisms based on tissue architecture


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# Agent Instructions
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## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

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```

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