LOTUS: Learning to Optimize Task-based US representations

Project Page | Paper | Data

Getting Started

You can install the required Python dependencies like this:

conda env create -f environment.yml
conda activate lotus

Reproducing results

The hyperparameters set in config/ can be used to reproduce the results from the paper. The data from the paper can be found in the release on GitHub, and the files should be placed in the datasets/ directory of this repository:

data
├── CT_labelmaps/
├── trainA_500/
├── GT_data_stopp_crit/
├── GT_data_testing/

For training run this command:

python train.py -c config/config_file.yml

For inferencing run this command:

python inference.py -c config/config_file.yml

Citation

@inproceedings{velikova2023lotus,
            title={LOTUS: Learning to Optimize Task-Based US Representations},
            author={Velikova, Yordanka and Azampour, Mohammad Farid and Simson, Walter and Gonzalez Duque, Vanessa and Navab, Nassir},
            booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
            pages={435--445},
            year={2023},
            organization={Springer}
          }