LabelCore.AI
LabelCore.ai
CT scan with AI radiology annotation overlays
Radiology Annotation

Radiology Annotation by Subspecialty Radiologists

CT, MRI, X-ray, ultrasound, PET, and mammography annotation with DICOM-native workflows. Every label traced to a credentialed radiologist.

Modalities We Annotate

CT Scans

Lung nodule detection, liver lesion segmentation, brain hemorrhage classification, cardiac CT analysis

MRI

Brain segmentation, cardiac MRI, musculoskeletal annotation, tumor volumetry

X-ray

Chest X-ray classification, bone fracture detection, dental annotation, foreign body detection

Ultrasound

Obstetric measurements, cardiac echo, abdominal organ segmentation, thyroid nodules

PET Scans

Oncology staging, neurological assessment, metabolic activity quantification

Mammography

Mass detection, calcification classification, density assessment, BI-RADS scoring

Annotation Types

Our radiologists apply the full spectrum of annotation types based on your AI model requirements:

  • ✓ Bounding boxes: fast object detection labels for lesions, nodules, and abnormalities
  • ✓ Polygon segmentation: precise boundary delineation for tumors, organs, and structures
  • ✓ Semantic segmentation: pixel-level classification for multi-structure analysis
  • ✓ 3D volumetric annotation: slice-by-slice annotation across CT and MRI volumes
  • ✓ Classification labels: multi-class and severity grading (e.g., BI-RADS, Lung-RADS)
  • ✓ Keypoint annotation: anatomical landmark detection for alignment and measurement

Why LabelCore for Radiology

Unlike crowd-sourced platforms that use non-medical workers, LabelCore.AI exclusively uses licensed radiologists matched to each imaging modality. A subspecialty-trained neuroradiologist annotates brain MRIs. A fellowship-trained breast imager annotates mammograms. This subspecialty matching is why our Gold Standard tier achieves 99% accuracy.

Every annotation includes clinical documentation, provenance chains traceable to the annotating physician, and inter-annotator agreement metrics. Our DICOM-native workflows mean no format conversion. Upload your imaging data and receive annotations in COCO, Pascal VOC, YOLO, or custom schemas.

Quality Tiers for Radiology

TierAccuracyMethodBest For
Gold Standard99%Multi-radiologist consensusFDA submissions, clinical trials
Hybrid93%AI pre-label + radiologist validationModel training, R&D
Ready Datasets85%Pre-labeled, instant downloadResearch, POC

Frequently Asked Questions

What radiology modalities does LabelCore annotate?+
LabelCore.AI annotates all major radiology modalities including CT scans, MRI, X-ray, ultrasound, PET scans, and mammography. Our radiologists are subspecialty-matched to each modality for maximum accuracy.
Do you support native DICOM workflows?+
Yes. LabelCore.AI provides DICOM-native annotation workflows. Upload DICOM files directly with no conversion needed. We preserve all metadata, support multi-frame and volumetric data, and export in standard formats.
What accuracy can I expect for radiology annotation?+
Our Gold Standard tier delivers 99% accuracy through multi-radiologist consensus with complete audit trails. Hybrid Intelligence provides 93% accuracy with 10x faster turnaround using AI-assisted pre-labeling with radiologist validation.
Can radiology annotations be used for FDA submissions?+
Yes. Gold Standard radiology annotations include full clinical documentation, provenance chains, and inter-annotator agreement metrics required for FDA 510(k), De Novo, and PMA submissions.
What annotation types are supported for radiology?+
We support bounding boxes, polygon segmentation, semantic segmentation, instance segmentation, keypoint annotation, 3D volumetric annotation, and classification labels for all radiology modalities.

Start Your Radiology Annotation Project

Tell us your modality, volume, and timeline. We match you with subspecialty radiologists within 48 hours.

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