OpenMind: Head-and-Neck 3D MRI Dataset for Self-Supervised Learning

114,000 3D MRI images of the head and neck region are pooled from 800 datasets on the OpenNeuro platform. The OpenMind Dataset, created by MIC-DKFZ, aims to accelerate the development of self-supervised learning methods for 3D medical imaging. It was last updated on the platform on April 3, 2025.

Use Cases

• Training self-supervised models for feature extraction based on 3D MRI volumes.
• Benchmarking representation learning algorithms based on large-scale medical imaging data.
• Developing pre-trained backbones for downstream medical vision tasks based on head and neck anatomy.

Strengths

• Contains 114,000 3D MRI images, providing a substantial volume for training.
• Aggregates data from 800 distinct source datasets, suggesting diversity in origin.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect source bias inherent to the OpenNeuro platform.

Provenance

Source

OpenNeuro platform

Collection Method

Pooled from 800 source datasets.

Freshness

Last updated 2025-04-03 11:51:07