Encord DICOM Tool: Medical Imaging Annotation Software
Encord DICOM Tool helps healthcare companies and medical AI teams label medical imaging data for model training. It is designed for organizations requiring HIPAA-compliant workflows and supports 3D annotations.
At a glance
- Category
- Healthcare
- Best for
- Healthcare AI development teams, Medical research institutions, Hospitals developing diagnostic tools, Medical imaging startups
- Pricing
- Pricing is available in three tiers: Starter for individuals and small teams, Team for scaling applications, and Enterprise for multi-team organizations. Pricing for the DICOM add-on was not explicitly detailed in the evidence; buyers should confirm current pricing on the vendor website.
- Key use cases
- Medical AI Training Data Generation, Vascular Ultrasound Analysis, Pathology Shape Capture, Dataset Curation
- Integrations
- AWS S3, Azure Data Lake Storage, Google Cloud Storage
- Official website
- encord.com/dicom/
Encord DICOM Tool is an annotation platform designed for medical imaging. It supports various formats, including DICOM and NIfTI files, to help teams create training data for medical AI models.
The tool is designed for healthcare companies, hospitals, and medical practices that need to label complex data such as CT scans, MRIs, and ultrasounds. It uses AI-assisted labeling to help reduce the manual effort required to create segmentation masks and object boundaries.
Beyond labeling, the platform supports collaborative workflows with consensus review stages and data curation tools. It is HIPAA compliant, which supports security standards when handling sensitive patient data.
Buyers should confirm if the pricing tiers—Starter, Team, and Enterprise—align with their specific needs for model evaluation, performance analytics, or on-premises deployment options.
Key Features
Uses the Segment Anything Model 2 and other automated capabilities to help create segmentation masks.
Supports 3D annotations and customizable layouts for medical imaging review.
Includes security controls designed to support the handling of sensitive medical data in accordance with HIPAA standards.
Supports the creation of no-code labeling pipelines with stages for annotation, review, and consensus.
Identifies series belonging to the same study using metadata for study-level labeling.
Interpolates labels across slices in DICOM files, which may reduce the number of images an annotator needs to label manually.
Use Cases
Creating annotated datasets from DICOM images for training computer vision models.
Segmenting inner and outer lumens in ultrasound images to support diagnostic research.
Using interpolation to capture the shape of pathologies across multiple imaging slices.
Filtering and slicing large medical datasets to identify and fix label errors.
Best For
Integrations
Pricing
Pricing is available in three tiers: Starter for individuals and small teams, Team for scaling applications, and Enterprise for multi-team organizations. Pricing for the DICOM add-on was not explicitly detailed in the evidence; buyers should confirm current pricing on the vendor website.
FAQ
Yes, Encord is HIPAA compliant and uses enterprise-grade practices and Vanta to verify its security and privacy controls.
The tool supports DICOM and NIfTI files, including data from CT, X-ray, MRI, Ultrasound, and Mammography.
No, Encord can connect to existing cloud infrastructure (such as AWS S3 or Google Cloud Storage) using signed URLs, which allows data to remain in your own storage.
Encord offers Starter for individuals, Team for those scaling a few applications, and Enterprise for companies with multiple AI applications across several teams.
Source category: Healthcare
Source subcategory: Medical Imaging Annotation
