Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images

David Hoar, Peter Q. Lee, Alessandro Guida, Steven Patterson, Chris V. Bowen, Jennifer Merrimen, Cheng Wang, Ricardo Rendon, Steven D. Beyea, Sharon E. Clarke. Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images. Computer Methods and Programs in Biomedicine, 210:106375, 2021. [doi]

@article{HoarLGPBMWRBC21,
  title = {Combined Transfer Learning and Test-Time Augmentation Improves Convolutional Neural Network-Based Semantic Segmentation of Prostate Cancer from Multi-Parametric MR Images},
  author = {David Hoar and Peter Q. Lee and Alessandro Guida and Steven Patterson and Chris V. Bowen and Jennifer Merrimen and Cheng Wang and Ricardo Rendon and Steven D. Beyea and Sharon E. Clarke},
  year = {2021},
  doi = {10.1016/j.cmpb.2021.106375},
  url = {https://doi.org/10.1016/j.cmpb.2021.106375},
  researchr = {https://researchr.org/publication/HoarLGPBMWRBC21},
  cites = {0},
  citedby = {0},
  journal = {Computer Methods and Programs in Biomedicine},
  volume = {210},
  pages = {106375},
}