Whole Slide Tissue Image Library

Successful AI models depend on access to high-quality, well-annotated, and clinically relevant data. AI-ready datasets typically combine high-resolution whole slide images with standardized quality control, verified annotations, comprehensive metadata, and linked clinical, molecular, and outcomes information.

Discovery's WSI datasets are curated to support a broad range of digital pathology and precision medicine applications, including: 

• Tumor detection and tumor burden assessment 

• Image classification and tissue segmentation 

• Biomarker discovery and validation 

• Cell type identification and spatial analysis 

• Treatment response and outcomes prediction 

• Multi-modal AI development that integrates pathology images with molecular, biomarker, and clinical data 

By combining high-quality whole slide images with rich contextual data, our customers can develop more accurate models and uncover insights that would be difficult to identify from image data alone.

While image data alone can provide valuable insights, combining pathology images with molecular, biomarker, clinical, and outcomes data allows researchers to build more powerful models. Multi-modal approaches can uncover relationships between tissue morphology, genomic alterations, treatment response, and patient outcomes that may not be apparent from any single data type.

Slide bank digitization converts physical tissue archives into research-ready digital assets that are easier to store, access, analyze, and share. Organizations often digitize slides to preserve valuable specimens, support remote pathology workflows, enable AI-driven analysis, and maximize the long-term value of their tissue collections. 

Many AI models are trained to recognize what is present in a tissue sample today. Outcomes data adds information about what happened to the patient over time, allowing developers to create models that predict treatment response, disease recurrence, progression, and survival. This can significantly increase the clinical utility of AI algorithms.