Multiplanar Editing
Edit annotations at exact slices and review the same structure across anatomical planes with synchronized crosshairs and geometry.
Medical Annotation Platform
Medical Annotation Platform for DICOM & Medical Imaging
Annotate DICOM, NIfTI, and NRRD medical imaging, including CT and MRI volumes, with synchronized multiplanar views, volumetric segmentation, clinical ontologies, and expert review.
No credit card required
Medical annotation features
Everything You Need for Complex Medical Annotation
Annotate DICOM volumes and medical imaging sequences, refine AI-assisted masks, and capture clinical context in one governed workspace.
Synchronized Multi-View
Work across axial, coronal, sagittal, and 3D views while positioning, windowing, and annotation context stay synchronized.
Medical Timelines & Sequences
Navigate frames and slices precisely while geometry, clinical states, and study-level context remain aligned.
Clinical Ontologies & Properties
Define classes, clinical findings, attributes, nested properties, relations, and study- or object-level context in one reusable medical schema.
Full Auto-Tracking
Track lesions, organs, or regions through complete medical sequences, or only forward or backward, then review generated tracks and correct keyframes that need expert judgment.
Bidirectional trackingForward trackingBackward tracking
Expert-reviewedAI-assisted
AI-Assisted Segmentation
Generate complex medical masks and regions faster, then refine boundaries and approve results under expert review.
Model proposalsHuman refinement
Why AI Teams Choose Unitlab for Medical Annotation
Accelerate expert labeling, automate repeatable work, and keep review and quality operations connected across medical datasets.
15X
Faster Medical Annotation
90%
Automated Medical Annotation
10X
Lower Annotation Costs
Supported medical annotation types
All medical annotation types in one platform.
Create volumetric masks, regions of interest, boxes, landmarks, measurements, properties, and relations across radiology studies and medical imaging sequences.
01
Bounding box
Mark rectangular findings, anatomy, lesions, and regions of interest across medical images or sequences.
02
Segmentation
Create pixel-accurate and volumetric masks for anatomy, lesions, tumors, and other clinical regions.
03
Polygon
Outline irregular findings and regions of interest across slices, frames, or medical sequences.
04
Skeleton
Model anatomical structures and articulated movement with connected keypoints.
05
Line / polyline
Trace vessels, boundaries, paths, contours, and measurement lines in medical data.
06
Point / keypoint
Place exact anatomical landmarks for localization, alignment, and keypoint tasks.
07
Cuboid / 3D box
Represent volumetric findings and anatomy with depth-aware 3D boxes.
08
Study / Item Properties
Describe modality, quality, cohort, procedure, and other whole-study attributes.
09
Relations
Connect anatomy, findings, observations, and related objects explicitly.
Medical dataset curation & annotation workflows
Curate medical data and automate annotation workflows.
Search, version, and inspect medical imaging studies and sequences, connect medical AI models, and route annotations through expert review and approval.
Dataset Versions
Version medical datasets, annotations, curated cohorts, and dataset changes while preserving traceability from source to release.
Semantic Search
Find relevant studies, scans, series, and similar cases across large medical imaging datasets without relying on manual folders.
Embedding View
Explore dataset distributions, similar cases, outliers, clusters, and potential data-quality problems before training.
Integrated Workflows
Connect annotation, expert review, QA, rework, and approval in structured medical workflows with clear ownership and traceable outcomes.
Bring Your Medical Model
Connect medical AI models for pre-labeling, segmentation, automation, and model-assisted annotation while keeping reviewers in control.
Solutions
Medical annotation solutions for imaging AI
Prepare radiology and longitudinal imaging datasets with precise, clinically structured annotations and governed expert review.
Radiology AI
Annotate CT, MRI, and other medical imaging studies for detection, segmentation, classification, and diagnostic AI development.
Explore healthcare solutions
Tumor & Lesion Segmentation
Create precise volumetric labels for tumors, lesions, abnormalities, and regions of clinical interest.
Explore healthcare solutions
Organ & Anatomy Segmentation
Annotate organs, anatomical structures, and tissue regions across synchronized axial, coronal, and sagittal views.
Explore healthcare solutions
Longitudinal Imaging Analysis
Label findings across multi-series and follow-up studies to train models for progression, treatment response, and temporal analysis.
Explore healthcare solutionsQuestions, answered
Medical Annotation Platform FAQs
Answers about DICOM annotation, CT and MRI imaging, NIfTI and NRRD volumes, synchronized multiplanar views, volumetric segmentation, clinical ontologies, and expert review in Unitlab.
Talk with the Unitlab teamWhat medical data and formats can Unitlab annotate?+
Unitlab supports medical imaging workflows for DICOM studies, CT and MRI series, NIfTI and NRRD volumes, and common image formats. Teams can annotate masks, regions, boxes, landmarks, measurements, classifications, properties, and relations in reusable medical ontologies. Whole-slide pathology workflows are covered on Unitlab’s dedicated Pathology Annotation page.
How does DICOM annotation work across axial, coronal, sagittal, and 3D views?+
DICOM studies open in synchronized axial, coronal, sagittal, and 3D views. Position, window and level, crosshairs, and annotation context stay aligned so experts can inspect and edit findings across planes.
Can Unitlab annotate pathology slides, medical sequences, and multiplanar studies?+
Yes. Unitlab supports slice-level multiplanar editing and frame- or slice-aware navigation for dynamic medical imaging sequences while preserving annotation context across synchronized views.
How do clinical ontologies, properties, and relations work in medical annotation?
Medical ontologies define anatomy, findings, classifications, nested properties, measurements, and relations. Static and dynamic properties capture clinical context at object, image, series, or study level.
Properties and relations documentationHow does Unitlab manage medical annotation review and quality assurance?+
Configurable workflows route tasks through expert annotation, review, rework, QA, and approval. Assignments, comments, issue tracking, history, dataset versions, and releases keep decisions traceable.
Annotation and review documentationCan teams use medical AI models for pre-labeling and segmentation?
Yes. Connect medical AI models for pre-labeling, segmentation, and model-assisted annotation. Experts review and refine predictions before approval, preserving human control.
Model integration documentationCan Unitlab curate and version medical datasets in one platform?
Yes. Teams can search, curate, annotate, review, and publish controlled versions of medical imaging datasets, including studies, scans, series, cohorts, annotations, and release changes.
Dataset management documentationMEDICAL ANNOTATION PLATFORM
Build Production-Ready Medical AI Datasets with Unitlab
Annotate, review, curate, and manage complex medical data in one collaborative AI-assisted platform.
