MambaRecon

Official Implementation for MambaRecon: MRI Reconstruction with Structured State Space Models. Recently featured at WACV 2025. Paper Link

Installation

Clone the repository:

git clone git@github.com:yilmazkorkmaz1/MambaRecon.git

Create the environment from the environment.yml:

conda env create -f environment.yml

Activate the environment:

conda activate mamba_recon_env

Install causal convolution and mamba packages:

cd casual-conv1d

python setup.py install

cd mamba

python setup.py install

Dataset

Download datasets and place them in datasets folder inside code:

https://drive.google.com/drive/folders/1XReBWt_oirOSdfc8rQf5OXIwdkxqX0xF?usp=share_link

Pretrained Checkpoint

Download pretrained checkpoints:

https://drive.google.com/drive/folders/1aPCqYbREsk5Q-vO8aXwDLFF51pe8XPCq?usp=share_link

Run Commands

python train.py --exp mamba_unrolled --dataset ixi --model mamba_unrolled --patch_size 2 --batch_size 4 --gpu_id 0

Citation

You are encouraged to modify/distribute this code. However, please acknowledge this code and cite the paper appropriately.

@InProceedings{Korkmaz_2025_WACV,
    author    = {Korkmaz, Yilmaz and Patel, Vishal M.},
    title     = {MambaRecon: MRI Reconstruction with Structured State Space Models},
    booktitle = {Proceedings of the Winter Conference on Applications of Computer Vision (WACV)},
    month     = {February},
    year      = {2025},
    pages     = {4142-4152}
}

Contact

ykorkma1[at]jhu.edu

Acknowledgements

We gratefully acknowledge the authors of the following repositories, from which we utilized code in our work: