Histopathology Annotation Services for Digital Pathology AI

Expert tissue sample annotation for cancer detection, cell classification, and pathology AI. Pathologist-supervised, HIPAA-compliant quality.

Why Histopathology Annotation Quality Matters

Digital pathology AI requires annotations that reflect true clinical expertise. Incorrect tumor boundaries or misclassified cells compromise diagnostic accuracy. AI Taggers delivers pathologist-supervised annotation that meets the precision demands of clinical-grade AI systems.

Trusted by pharmaceutical companies, diagnostic laboratories, and digital pathology startups to build regulatory-ready training datasets.

Our Histopathology Annotation Capabilities

Tumor Region Segmentation

Pixel-precise delineation of malignant tissue, tumor margins, and invasion patterns in H&E stained sections. Essential for cancer grading AI and surgical margin assessment tools.

Cell Type Classification

Individual cell annotation including lymphocytes, macrophages, epithelial cells, and stromal components. Training data for digital pathology and immuno-oncology AI systems.

Tissue Architecture Labeling

Annotation of glandular structures, blood vessels, nerve bundles, and tissue organization patterns. Critical for understanding disease progression and treatment response.

Mitotic Figure Detection

Precise identification and labeling of mitotic figures for cancer grading algorithms. High-accuracy annotation following established pathology scoring criteria.

Immunohistochemistry Quantification

Annotation of IHC-stained slides including marker intensity scoring, positive/negative cell counting, and staining pattern characterization.

Multi-Stain Analysis

Coordinated annotation across serial sections with different stains including H&E, IHC markers, and special stains for comprehensive tissue characterization.

Pathology-Grade Quality Standards

Our histopathology workflows integrate clinical expertise at every stage with pathologist oversight and reproducible protocols.

Pathologist-Verified Labels

All histopathology annotations reviewed by board-certified pathologists with subspecialty expertise in relevant tissue types.

HIPAA & CAP Compliance

Annotation workflows meet healthcare privacy requirements and laboratory accreditation standards for clinical AI development.

Whole Slide Image Processing

Native handling of gigapixel WSI formats including SVS, NDPI, and MRXS with efficient region-of-interest workflows.

Reproducible Annotation Protocols

Standardized labeling criteria with inter-observer variability tracking and consensus resolution procedures.

Scalable Whole Slide Image Annotation

From pilot validation to large-scale training datasets, we maintain pathologist-level quality across gigapixel whole slide images.

99.2%

Annotation accuracy rate

100%

Pathologist reviewed

WSI

Native format support

Industries We Serve

Pharmaceutical Companies

Drug development studies, biomarker validation, clinical trial pathology analysis, and companion diagnostic development.

Diagnostic Laboratories

Training AI-assisted screening tools, second-opinion systems, and workflow optimization for high-volume pathology practices.

Academic Medical Centers

Research dataset creation, rare disease studies, multi-center trial standardization, and AI publication support.

Digital Pathology Vendors

Algorithm training for slide scanners, image analysis platforms, and computer-aided detection systems.

Biotech Startups

Building tissue-based biomarker discovery platforms, precision medicine tools, and novel therapeutic targeting systems.

Contract Research Organizations

Standardized pathology endpoints for clinical trials, treatment response assessment, and regulatory submission support.

Why Pathology AI Teams Choose AI Taggers

Pathologist Expertise

Annotation teams trained by subspecialty pathologists with disease-specific certification.

Regulatory Ready

Documentation and quality metrics structured for FDA 510(k) and CE marking submissions.

Multi-Format Support

Native handling of all major WSI formats with metadata preservation and export flexibility.

Secure PHI Handling

De-identification services, encrypted workflows, and strict access controls for patient data.

Our Histopathology Annotation Process

1

Pathology Consultation

We review your tissue types, staining protocols, and annotation taxonomy with pathologist input to develop clinically accurate guidelines.

2

Calibration Phase

Annotate representative slides with pathologist review. Establish inter-annotator agreement metrics before production.

3

Production Annotation

Trained annotators label your WSI dataset with continuous QA and pathologist oversight on complex cases.

4

Expert Validation

Final pathologist review with delivery in your preferred format including GeoJSON, ASAP XML, or QuPath compatible outputs.

Real Results From Pathology AI Teams

"The histopathology annotation quality matched our in-house pathologists' standards. Their expertise in tumor segmentation accelerated our oncology AI development."

Head of Computational Pathology

Pharmaceutical Company

"AI Taggers handled our complex IHC scoring requirements with precision. The pathologist oversight gave us confidence for our FDA submission."

Director of AI Research

Diagnostic AI Company

Get Started With Expert Histopathology Annotation

Whether you're building cancer detection AI, training cell classification models, or developing digital pathology platforms, AI Taggers delivers the clinical-grade annotation your pathology AI requires.

Questions about histopathology annotation?

What tissue types need annotation?

What staining protocols are used?

Do you need tumor segmentation or cell counting?

What WSI scanner format are your slides in?

Our pathology annotation team responds within 24 hours with a tailored solution for your digital pathology AI project.