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

科研成果: 期刊稿件文章同行评审

27 引用 (Scopus)
源语言英语
文章编号106375
期刊Computer Methods and Programs in Biomedicine
210
DOI
出版状态已出版 - 10月 2021

!!!ASJC Scopus Subject Areas

  • 软件
  • 卫生信息学
  • 计算机科学应用

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Hoar, D., Lee, P. Q., Guida, A., Patterson, S., Bowen, C. V., Merrimen, J., Wang, C., Rendon, R., Beyea, S. D., & Clarke, S. E. (2021). 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, 文章 106375. https://doi.org/10.1016/j.cmpb.2021.106375