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spectraMR: A Multi-Paradigm Research Framework for MRI Reconstruction, Super-Resolution, and Generative Modelling

spectraMR is a research framework for MRI reconstruction, super-resolution and generative modelling. It spans GAN, diffusion (including cold and latent diffusion), VAE/VQ-VAE, masked-autoencoder and self-supervised pretraining, reconstruction-only, domain-adaptation, physics-driven, disentangled, sensitivity-estimation (PINN), cycle-Bloch, flow, state-space (Mamba), magnetic-resonance-fingerprinting, fMRI and active/learnable-acquisition paradigms behind one configuration schema. Complex k-space is handled through centred, orthonormally-scaled FFT operators rather than raw transforms; configuration is nested, frozen and loaded once; component

Resource information

Format
zip
Original repository
23905823
DOI
10.5281/zenodo.23905823
Credit basis
Creators in Zenodo record metadata
Access
Open files available from the original Zenodo deposit
Last checked
Nov 5, 2026
License
apache2.0
Last record update
Nov 5, 2026

About this resource

spectraMR is a research framework for MRI reconstruction, super-resolution and generative modelling. It spans GAN, diffusion (including cold and latent diffusion), VAE/VQ-VAE, masked-autoencoder and self-supervised pretraining, reconstruction-only, domain-adaptation, physics-driven, disentangled, sensitivity-estimation (PINN), cycle-Bloch, flow, state-space (Mamba), magnetic-resonance-fingerprinting, fMRI and active/learnable-acquisition paradigms behind one configuration schema. Complex k-space is handled through centred, orthonormally-scaled FFT operators rather than raw transforms; configuration is nested, frozen and loaded once; components resolve through registries and a dependency-injection container rather than dispatch chains. Heavy pipelines run on an accelerator or raise, with no silent CPU fallback. Not for clinical use. This is research software. It is not a medical device and has not been evaluated by any regulatory authority.