radiology

Radiology

Pareidolia Systems is your trusted partner for outsourced medical image annotation for AI, providing accurate medical imaging QC for AI models and serving as the best medical image segmentation provider for healthcare innovators. We empower radiology startups and deep learning research with high-fidelity AI training data and a scalable annotation team for healthcare AI..

radiology
radiology

Accurate Medical Imaging QC for AI Models

Our clinical specialists and certified annotators provide pixel-level precision labeling across all major modalities: X-ray, CT, MRI, ultrasound, mammography, digital breast tomosynthesis, PET, and DEXA scans. We meticulously label anatomical structures, lesions, and abnormalities, covering diverse disease states and complex imaging challenges.

Every dataset we create undergoes rigorous validation and accurate medical imaging QC for AI models to ensure anatomical accuracy, compliance, and consistency. This pareidolia’s commitment to quality empowers you to build reliable, clinically validated AI models that enhance diagnosis, treatment, and improve patient outcomes.

radiology
radiology

Scalable Annotation Team for Healthcare AI

Pareidolia Systems LLP offers a scalable annotation team for healthcare AI, combining deep domain expertise with advanced annotation tools to efficiently create medical datasets for machine learning. We empower healthcare innovators to accelerate imaging-driven medical breakthroughs across all segments:

Types of Medical Image Annotation in Radiology

X-ray Annotation & Segmentation:

Expert labeling of bones, lungs, joints, fractures, and tumors, validated for clinical precision to power reliable AI diagnostic models.

CT Scan Annotation & Segmentation:

Detailed slice by slice annotation of organs, vessels, lesions, and hemorrhages with pixel-level accuracy, supporting high-quality diagnosis and surgical planning AI.

MRI Annotation & Segmentation:

Precise musculoskeletal and soft tissue annotation, including infarct, edema, tears, and tumors, to enable advanced AI-driven diagnostic tools.

Ultrasound Annotation & Segmentation:

Annotation of dynamic soft tissue, vascular, abdominal, and obstetric scans, ensuring high-quality data for diverse clinical AI applications.

Mammography & Tomosynthesis Annotation:

Specializing in labeling masses, calcifications, and architectural distortions for precise AI-driven breast cancer detection and risk assessment.

PET Scan Annotation:

Focusing on metabolic and functional imaging, tagging areas of abnormal tracer uptake to facilitate AI models that enhance disease staging.

DEXA Scan Annotation:

Labeled datasets for bone density and body composition analysis, helping AI systems accurately assess osteoporosis risk and metabolic conditions.

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