A Deep Learning method to segment punctate white matter lesions (PWMLs); Brain tumor segmentation.
By: Yalong Liu¹, Jie Li¹, Ying Wang¹, Miaomiao Wang², Xianjun Li², Zhicheng Jiao³, Jian Yang², Xingbo Gao¹

1. Lab of Video and Image Processing Systems, School of Electronic Engineering, Xidian University, Xi’an 710071, China
2. Department of Radiology, The First Affiliated Hospital of Xi'an Jiaotong University, Xi’an 710061, China
3. University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA

This repository includes:
1.T1WI of 10 patients for test(Full dataset is not allowed to be made public)
2.Full code for model training and inference
3.The link of pre-trained weights on google drive

Python 3.6.3
Tensorflow-gpu 1.12.0
CUDA 9.0

1.Download the repositories and weights.
2.Choose a mode in the main.py('inference' or 'training').
3.(optional)Change parameters in configs.py according to the comment in the file.
4.python ./main.py
Enjoy!

This repo borrows tons of code from
matterport/Mask_RCNN

Performance:

8/77
79/67
82/67
83/48
83/54
83/80

If you use Refined Segmentation R-CNN in your research, please cite the paper (http://arxiv.org/abs/1906.09684):

@article{Liu2019,
  title={Refined Segmentation R-CNN: A Two-stage Convolutional Neural Network for Punctate White Matter Lesion Segmentation in Preterm Infants},
  author={Yalong Liu, Jie Li, Ying Wang, Miaomiao Wang, Xianjun Li, Zhicheng Jiao, Jian Yang, Xingbo Gao},
  journal={arXiv preprint arXiv:1906.09684},
  year={2019}
}