Better data starts with better annotation.
The quality of your annotations directly impacts the quality of your models. But for many research teams, annotation quickly becomes one of the most time-consuming parts of the AI development process.
Managing datasets across multiple contributors, maintaining consistent labels, reviewing completed work, and preparing data for model training can slow projects down before they ever reach experimentation.
Datamint brings your entire annotation workflow into one platform, helping research teams stay organized while producing high-quality datasets with confidence.
Annotate medical imaging data with confidence.
Whether you're working with radiology images, microscopy slides, or other medical imaging datasets, Datamint provides flexible annotation tools designed to support real-world research workflows.
We support a variety of annotation methods so your team can label data in the way that best fits your project.
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Bounding boxes
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Polygons
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Classification labels
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Keypoints
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Measurements and geometry
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Custom labels
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Segmentations
As your research evolves, your workflows evolve with it.
Multiple Annotation Types
Speed up repetitive tasks without sacrificing accuracy. Datamint's AI-assisted annotation capabilities help researchers accelerate the labeling process while keeping humans in control. Generate initial segmentations and make adjustments before they're finalized.
The result is faster dataset creation while maintaining the quality your research depends on.
AI-Assisted Annotation
Consistent annotations lead to better models.
Datamint makes it easy to review completed annotations, validate labeling consistency, and approve work before it's added to your training dataset.
Built-in review workflows help research teams reduce errors and improve reproducibility across projects.
Annotation Review & Quality Control
Unlike general-purpose annotation platforms, Datamint is designed specifically for medical AI research.
Support for medical imaging workflows, research datasets, and collaborative teams means you spend less time adapting your tools—and more time advancing your research.
Built specifically for Medical Imaging
From raw images to AI-ready datasets.
Building an AI model starts long before training begins. Datamint helps research teams move through every stage of dataset preparation with a streamlined workflow.
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Import
Upload medical imaging datasets and organize your research projects.
Organize
Structure datasets with metadata, labels, and project-specific organization.
Annotate
Collaboratively annotate images using flexible annotation tools built for medical research.
Review
Validate completed annotations through structured quality assurance workflows.
Export
Generate clean, well-organized datasets ready for model development and experimentation.
Why researchers choose Datamint.
Annotation is rarely a one-person job.
Researchers, graduate students, clinicians, and collaborators often work together across multiple projects and institutions. Datamint keeps everyone aligned with centralized project management, clear task assignments, and shared annotation workflows.
Instead of managing spreadsheets, file transfers, and disconnected software, your team can work from one collaborative platform that keeps every project organized from beginning to end.
With Datamint, you can:
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Assign annotation tasks to team members
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Monitor project progress in real time
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Review completed work before approval
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Keep datasets organized and searchable
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Collaborate across departments and institutions
Why researchers choose Datamint.
Designed for research
Datamint was built around the way research teams actually work, with workflows that support collaboration, reproducibility, and long-term projects.
Faster annotation workflows
Reduce administrative overhead and spend more time generating high-quality training data.
Better collaboration
Keep researchers, students, and collaborators working from one centralized platform instead of juggling disconnected tools.
Consistent, reproducible datasets
Standardized workflows and built-in review processes help improve annotation quality across every project.
More than annotation software
Datamint combines annotation, dataset management, experiment tracking, and project organization into one connected research platform.
Continue exploring Datamint.
Looking for more than annotation? Explore how Datamint supports every stage of the AI research lifecycle.