Annotate DICOM and NIfTI images 6x faster

Quickly label large training datasets from modalities including CT, X-ray, and MRI and reduce AI model development time by up to 80%.

Trusted by pioneering AI teams

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How it works

The first purpose-built DICOM annotation tool for healthcare AI

Encord's medical imaging labeling tool supports a range of file formats, including DICOM and NIfTI. It has been developed in close collaboration with clinicians and healthcare data science experts to deliver maximal functionality and an unparalleled user experience. Learn more about healthcare applications.

Hanging protocols

Expert tool navigation & display manipulation.

  • Measurements
  • Magnify & zoom
  • Window widths & levels

3D view

Seamlessly toggle between different viewports.

  • Axial view
  • Coronal view
  • Sagittal view

Fully auditable

Our system keeps an audit trail of every single label you produce.

  • Monitor annotator quality
  • Expert review
  • Fully auditable labels

Cropped DICOM image

Annotate in three dimensions

The first DICOM annotation tool with truly native 3D annotation capabilities and windows defineable by Hounsfield units. Use pre-set windows or customise your own.

DICOM interpolation

Automate annotations

Use our bounding box, polygon, and segmentation interpolation feature to make the most of human supervision. Use native model-assisted labeling to accelerate your active learning pipelines.

Use cases

Accelerating AI in healthcare

Encord's software empowers some of the world's leading companies building computer vision models for medical imaging. Learn more about our clinical operations capabilities.

Computed tomography

Analyse and annotate voxels in CT with super-human precision.

  • Stroke detection
  • Pulmonary embolism diagnosis
  • Colonography

Magnetic resonance imaging

Use pre-set or custom windows in MRI using the Hounsfield scale.

  • Brain aneurysm segmentation
  • Tumor classification
  • Cyst localisation

X-ray

Classify X-rays at unparalleled efficiency.

  • Lesion tracking
  • Oncology monitoring
  • Pneumonia diagnosis
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Memorial Sloan Kettering Cancer Center

MSK adopted Encord to build custom label structures for pulmonary thrombosis projects.

Problem
Detecting and classifying vena cava filters in complex label structures (ontologies) rendered existing & open-source tools unusable.
Solution
Deployed Encord's ontology studio to build custom ontologies, DICOM annotation tool, & automation modules to increase efficiency.
Results
Project made feasible by the flexibility offered by Encord's ontology study.
1000+
Feature types
10 minutes
Total setup time
100%
Auditable

Experience Encord in action