git clone git+https://github.com/andreped/PLS-Net
cd "PLS-Net"
pip install -r requirements.txt

from PLS_pytorch import PLS
network = PLS()

from PLS_lightning import PLS
network = PLS()

@article{bouget2021code,
  author = {David Bouget and Andr{\'e} Pedersen and Sayied Abdol Mohieb Hosainey and Johanna Vanel and Ole Solheim and Ingerid Reinertsen},
  title = {{Fast meningioma segmentation in T1-weighted magnetic resonance imaging volumes using a lightweight 3D deep learning architecture}},
  volume = {8},
  journal = {Journal of Medical Imaging},
  number = {2},
  publisher = {SPIE},
  pages = {024002},
  keywords = {three-dimensional segmentation, deep learning, meningioma, magnetic resonance imaging, clinical diagnosis, Magnetic resonance imaging, Image segmentation, Tumors, Brain, 3D image processing, 3D modeling, Image resolution, Data modeling, Neural networks, Surgery},
  year = {2021},
  doi = {10.1117/1.JMI.8.2.024002},
  url = {https://doi.org/10.1117/1.JMI.8.2.024002}
}

@misc{lee2019plsnet,
  author = {Lee, Hoileong and Matin, Tahreema and Gleeson, Fergus and Grau, Vicente},
  title = {{Efficient 3D Fully Convolutional Networks for Pulmonary Lobe Segmentation in CT Images}},
  publisher = {arXiv},
  year = {2019},
  copyright = {arXiv.org perpetual, non-exclusive license},
  keywords = {Image and Video Processing (eess.IV), Computer Vision and Pattern Recognition (cs.CV), FOS: Electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, FOS: Computer and information sciences, FOS: Computer and information sciences},
  doi = {10.48550/ARXIV.1909.07474},
  url = {https://arxiv.org/abs/1909.07474}
}