Coronary Arteries Segmentation with SegMamba

This repository hosts the implementation for Coronary Arteries Segmentation, employing the innovative SegMamba framework.

About SegMamba

SegMamba offers a cutting-edge approach to coronary arteries segmentation, providing robust and accurate results. By leveraging advanced techniques, SegMamba optimizes the segmentation process, ensuring high-quality outputs.

Getting Started

Follow these steps to set up the SegMamba environment and begin your experiments:

1. Clone SegMamba Repository: Start by cloning the SegMamba repository from here. Follow the installation instructions provided in the repository to set up the environment.

2. Clone this Project: Clone the Coronary Arteries Segmentation project repository.

3. Activate Environment: Ensure your environment is activated and all dependencies are installed as per the instructions in the SegMamba repository.

4. Run Experiments: Utilize the main.py script to execute your experiments seamlessly within the SegMamba framework.

Additional Models

For Unet and Mamba-Encoder models, clone the LightM-UNet repository from here and follow the instructions provided in the repository.

With SegMamba and LightM-UNet, you have a comprehensive toolkit for coronary arteries segmentation, empowering you to achieve state-of-the-art results.