Xiaoqi Zhao, Lihe Zhang, Huchuan Lu
⭐ arXiv »
Xiaoqi Zhao, Hongpeng Jia, Youwei Pang, Long Lv, Feng Tian, Lihe Zhang, Weibing Sun, Huchuan Lu
⭐ arXiv »
Dataset.Config(datapath='', savepath='', mode='train', batch=16, lr=0.05, momen=0.9, decay=5e-4, epoch='')
%the number of training epochs settings in the polyp segmentation, COVID-19 Lung Infection, breast tumor segmentation and OCT layer segmentation are 50, 200, 100 and 100, respectively.
python train.py
[ ] 3D verison MSNet training.
[ ] Support different backbones (VGGNet, MobileNet, ResNet, Swin, etc.).
[ ] Diverse Medical Image Segmentation
@inproceedings{MSNet,
title={Automatic polyp segmentation via multi-scale subtraction network},
author={Zhao, Xiaoqi and Zhang, Lihe and Lu, Huchuan},
booktitle={MICCAI},
pages={120--130},
year={2021},
organization={Springer}
}
@article{M2SNet,
title={M $\^{}$\{$2$\}$ $ SNet: Multi-scale in Multi-scale Subtraction Network for Medical Image Segmentation},
author={Zhao, Xiaoqi and Jia, Hongpeng and Pang, Youwei and Lv, Long and Tian, Feng and Zhang, Lihe and Sun, Weibing and Lu, Huchuan},
journal={arXiv preprint arXiv:2303.10894},
year={2023}
}