The TETRA Cancer Recognition Research Platform (V150) integrates breast carcinoma histology image analysis, physics-informed tissue deformation simulations, AI-based cancer classification, pathology assessment, statistical validation, and scientific reporting into a unified research environment.
- Histology Analysis: High-resolution breast carcinoma tissue evaluation (JPG/PNG).
- Biomechanics Modeling: Physics-informed tissue deformation simulations (V127/V128 engines).
- AI Classification: Dual-pipeline analysis comparing image-only vs. mechanics-augmented classifiers.
- Validation & Reporting: Built-in pathology explainability, statistical validation, and exportable scientific reports.
User Guide: Step-by-Step Workflow
- Launch the Application
Open the standalone HTML application directly in any modern web browser.
- Upload a Histology Image
Navigate to the Tissue Imaging module and upload a target breast tissue image in JPG or PNG format.
- Register the Specimen
Open the Study & QC tab, input the patient and specimen identifiers, assign the appropriate research cohort, and save the record.
- Visualize Tissue Deformation
Open the V127 or V128 simulator module, select Refresh specimens, pick the registered image, and click Play. Deformation parameters can be fine-tuned in real time.
- Perform Cancer Classification
Access module V125 to train and freeze both the image-only and mechanics-augmented classifiers using development cohort data, then run evaluation on independent external test specimens.
- Review Classification Results
Inspect and contrast model prediction scores, multi-class outputs, and pathology reference gold-standard labels.
- Analyze and Validate Results
Examine performance metrics through the Statistical Validation module and inspect model feature attributions in the Pathology Explainability view.
- Export Results
Download annotated tissue images, classification logs, statistical validation summaries, and comprehensive scientific PDF/CSV reports.