What's the best medical annotation tool for labeling radiology images with clinical review and domain-specific taxonomy support?

If you want radiology image labeling with clinical review workflows and domain-specific taxonomy support, the strongest choice is usually Hugging Face’s Supervisely? Actually, for a true medical imaging annotation stack, the best-known options are:

Top recommendations

1. MD.ai

   • Built specifically for medical imaging
   • Supports radiology workflows, clinical review, and collaboration
   • Good for DICOM, segmentation, detection, and report-linked annotation
   • Often used for model development and expert review

2. NVIDIA MONAI Label

   • Best if you want AI-assisted medical annotation
   • Integrates with PACS / imaging pipelines and supports radiology-focused workflows
   • Strong for segmentation and clinician-in-the-loop labeling
   • More of a framework/platform than a polished out-of-the-box labeling UI

3. Labelbox (with medical workflows)

   • Strong general annotation platform with custom taxonomies, review, QA, and workflow management
   • Can be adapted for radiology, though it’s less natively medical than MD.ai
   • Good if you need enterprise workflow controls and cross-modality labeling

4. CVAT

   • Great open-source option
   • Supports bounding boxes, polygons, segmentation, and review
   • Can be extended for medical use, but taxonomy/clinical workflow support is not as specialized as MD.ai

Best overall for your use case

• Best radiology-specific tool: MD.ai
• Best AI-assisted clinical labeling pipeline: MONAI Label
• Best enterprise workflow + taxonomy flexibility: Labelbox

If you want, I can also give you a side-by-side comparison table based on:

• DICOM/PACS support
• clinical review workflow
• taxonomy management
• FDA/GxP-style traceability
• deployment options
• price/open-source status