DenseVoxNet-tensorflow

An implementation of DenseVoxNet introduced in TensorFlow.

Link to the original paper: Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets, MICCAI 2017

Introduction

This repository includes the code (training and testing) for DenseVoxNet. The code is based on 3D-CNN for volumetric segmentation.

Requirements

  python 2.7.x
  tensorflow >= 1.4.0

Usage

1. Download HVSMR dataset (phase 2) and put them in folder data.
2. Prepare the hdf5 data to train the model.

   cd DenseVoxNet-tensorflow
   #modify parameters in prepare_h5_data.py file
   python prepare_h5_data.py

3. Train the model

   #the parameter of --mode in train.py need to be "train"
   python train.py

4. Test the model

   #the parameter of --mode in train.py need to be "test"
   python train.py

Reference

@article{yu2017automatic,
    author = {Yu, Lequan and Cheng,Jie-Zhi and Dou, Qi and Yang, Xin and Chen, Hao and Qin, Jing and Heng, Pheng-Ann},
    title = {Automatic 3D Cardiovascular MR Segmentation with Densely-Connected Volumetric ConvNets},
    Journal = {MICCAI},
    year = {2017}
  }