ASSAN

This repo contains the offical PyTroch code for Sparse Reconstruction of Optical Doppler Tomography with Alternative State Space Model and Attention @ MICCAI 2025

Overview

Result

Preparation

To bulid the environment：

conda env create -f environment.yaml

If you meet compatibility issues, you may need to reinstall pytorch and torchvision:

pip uninstall torch torchvision torchaudio
pip install torch==2.3.1 torchvision==0.18.1 torchaudio==2.3.1 --index-url https://download.pytorch.org/whl/cu118

Checkpoints and example data are available at data link.

For data preparation, simply put the shared data folder and the checkpoint file under the root of this repo. The training data is splited along the width for faster loading.

Instructions

For training on x2 sparsity:

OMP_NUM_THREADS=4 torchrun --nnodes=1 --nproc_per_node=4 odt_train.py --sp 2 --batch-size 2

For testing on x2 sparsity:

python odt_test.py --sp 2

Acknowledgments

This repo mainly refers to Mamba and VMamba for the implementation of Mamba.

Citation

@inproceedings{li2025sparse,
  title={Sparse Reconstruction of Optical Doppler Tomography with Alternative State Space Model and Attention},
  author={Li, Zhenghong and Ren, Jiaxiang and Cheng, Wensheng and Liu, Yanzuo and Du, Congwu and Pan, Yingtian and Ling, Haibin},
  booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
  year={2025}
}