Datature Medical AI Suite: Label, Train, and Deploy 3D Models

Datature's Medical AI Suite brings the full computer vision pipeline to medical imaging: upload DICOM and NIfTI data, annotate in 3D with MPR tools, train segmentation models like Swin UNETR and nnU-Net, and deploy to API or edge. This overview covers what the suite includes and how the pieces connect.

What the Medical AI Suite Includes

• Native DICOM/NIfTI support with automatic series grouping and spatial metadata preservation
• 3D annotation workspace with multi-planar reconstruction (axial, coronal, sagittal views)
• 3D Slicer integration for teams already using open-source medical imaging tools
• Medical segmentation models including Swin UNETR, SegResNet, and nnU-Net
• Deployment options including cloud API and self-hosted GPU runners for HIPAA-compliant environments

Why a Dedicated Medical Suite

General-purpose annotation platforms bolt medical imaging on as an afterthought. The result: broken DICOM parsing, no 3D viewer, and segmentation tools that only work on 2D slices. Datature built the medical suite from the ground up for volumetric data, so the annotation tools, training pipelines, and deployment options all understand 3D natively.

Start Here, Then Go Deeper

• Upload DICOM and NIfTI Files to Datature Nexus
• How to Annotate 3D Medical Scans
• Train a 3D Medical Segmentation Model with Swin UNETR
• BrainScanology: Building Medical AI Models on Datature