NeuroCBIR: A Fast and Accurate Image Retrieval System for Whole-Brain and Region-Specific MRI

cs.CV, cs.LG, q-bio.NC

Submitted: 2026-10-05

Updated: 2026-10-05

Comments: Neuroimaging, Content-Based Image Retrieval, MRI, Zero-Shot Learning

Code: https://github.com/minnelab/NeuroCBIR

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Sources

• MONAI: An open-source framework for deep learning in healthcare
• Med3D: Transfer Learning for 3D Medical Image Analysis
• A Simple Framework for Contrastive Learning of Visual Representations
• Deep Residual Learning for Image Recognition
• GANs Trained by a Two Time-Scale Update Rule Converge to a Local Nash Equilibrium
• UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction
• Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge
• Loc-VAE: Learning Structurally Localized Representation from 3D Brain MR Images for Content-Based Image Retrieval
• Efficient feature embedding of 3D brain MRI images for content-based image retrieval with deep metric learning
• High-Resolution Image Synthesis with Latent Diffusion Models
• Domain-invariant feature learning in brain MR imaging for content-based image retrieval
• Large-Scale 3D Medical Image Pre-training with Geometric Context Priors

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