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UDBRNet: A Novel Uncertainty Driven Boundary Refined Network for Organ at Risk Segmentation

This repository will contain the source code related to the research paper titled "UDBRNet: A Novel Uncertainty Driven Boundary Refined Network for Organ at Risk Segmentation".

Paper

Paper: Link

Contact

For any kind of help or collaboration, Email Riad Hassan.

Necessary Packages and Versions

numpy~=1.26.2
matplotlib~=3.8.2
tqdm~=4.66.1
monai~=1.3.0
torch~=2.1.2
scipy~=1.13.0

Run the code

python train.py --dataset 'dataset_name' --data_path 'dataset_directory' --model_name 'UDBRNet'

Output

3D view of segmented organs for SegThor dataset

3D output for SegThor dataset

3D view of segmented organs for LCTSC dataset

3D output for LCTSC dataset

Predicted (Green) and ground truth (Red) contoured output for SegThor dataset

Contoured output for SegThor dataset

Predicted (Green) and ground truth (Red) contoured output for LCTSC dataset

Contoured output for LCTSC dataset

Cite this work

@article{10.1371/journal.pone.0304771,
    doi = {10.1371/journal.pone.0304771},
    author = {Hassan, Riad AND Mondal, M. Rubaiyat Hossain AND Ahamed, Sheikh Iqbal},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation},
    year = {2024},
    month = {06},
    volume = {19},
    url = {https://doi.org/10.1371/journal.pone.0304771},
    pages = {1-18},
    number = {6},
}

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UDBRNet: A novel uncertainty driven boundary refined network for organ at risk segmentation

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