Framelet Regularized SENSE Calibration in K-Space with Conditional Sensitivity-Map Updates Algorithm (ComeUs)

This repository provides the official implementation of Framelet Regularized SENSE Calibration in K-Space with Conditional Sensitivity-Map Updates Algorithm.

🔧 Requirements

The environment configuration is provided in environment.yml. You can create the environment using:

conda env create -f environment.yml

🚀 Getting Started

To run the reconstruction on test data:

python main.py

The code includes a set of Phantom data for quick testing.

📁 Project Structure

• main.py – Entry point for running the reconstruction.
• gen_mask.m – MATLAB script for generating sampling masks.
• environment.yml – Conda environment specification.
• data/ – Contains example Phantom test data.
• mask/ – Contains example undersampled mode.
• algorithm/ADDL.py – Our propose ADDL algorithm.
• utils/ – Supporting modules.

📦 Additional test data

Additional test data is available at:

👉 Google Drive - Test Data

• Generate your own sampling patterns via gen_mask.m.
• If there have any problem, please send an email to 2019151068@email.szu.edu.cn