I3Net: Inter-Intra-slice Interpolation Network for Medical Slice Synthesis (TMI 2024)

Haofei Song, Xintian Mao, Jing Yu, Qingli Li, Yan Wang

Paper: https://doi.org/10.1109/TMI.2024.3394033 or http://arxiv.org/abs/2405.02857.

Requirements

This repository is based on PyTorch 1.12.0, CUDA 11.3 and Python 3.8.13.

Data Preparation

Data obtain:

• CT: From Medical Decathlon Challenge (MSD), specifically from the Liver, Colon, and Hepatic Vessel dataset. Data split using test_set.pt from SAINT.

• MR: From IXI, collected at Hammersmith Hospital.

Data process:

• Split trainset and testset using step1_split.py.
• Save each slice using step2_save_slice.py.

Quick run

To test a model:

bash test.sh

To train a model:

bash train.sh

Citation

@article{Song_2024,
   title={I³Net: Inter-Intra-slice Interpolation Network for Medical Slice Synthesis},
   url={http://dx.doi.org/10.1109/TMI.2024.3394033},
   DOI={10.1109/tmi.2024.3394033},
   journal={IEEE Transactions on Medical Imaging},
   publisher={Institute of Electrical and Electronics Engineers (IEEE)},
   author={Song, Haofei and Mao, Xintian and Yu, Jing and Li, Qingli and Wang, Yan},
   year={2024},
   volume={43},
   number={9},
   pages={3306-3318},
 }

Contact

If you have any question, please contact [email protected]