This is the official Pytorch implementation of LoTeNet model in "Tensor Networks for Medical Image Classification", Raghavendra Selvan & Erik Dam, MIDL 2020. Runner up for the best paper award at MIDL2020.
- Run and reproduce results in the paper on LIDC dataset
- v1.0
- Basic Pytorch dependency
- Tested on Pytorch 1.3, Python 3.6
- Download the data from here
- Unzip the data and point the path to --data_path
- How to run tests: python train.py --data_path data_location
- Kindly cite our publication if you use any part of the code
@inproceedings{
raghav2020tensor,
title={Tensor Networks for Medical Image Classification},
author={Raghavendra Selvan, Erik B Dam},
booktitle={International Conference on Medical Imaging with Deep Learning -- Full Paper Track},
year={2020},
month={July},
url={https://openreview.net/forum?id=jjk6bxk07G}}
- Torch MPS for the amazing MPS in Pytorch implementations
- Prob.U-Net for preprocessing LIDC data
- Dense Net implementation