Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images

@article{Wang2020BendingLR,
  title={Bending Loss Regularized Network for Nuclei Segmentation in Histopathology Images},
  author={Haotian Wang and Min Xian and Aleksandar Vakanski},
  journal={2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)},
  year={2020},
  pages={1-5}
}
Separating overlapped nuclei is a major challenge in histopathology image analysis. Recently published approaches have achieved promising overall performance on public datasets; however, their performance in segmenting overlapped nuclei are limited. To address the issue, we propose the bending loss regularized network for nuclei segmentation. The proposed bending loss defines high penalties to contour points with large curvatures, and applies small penalties to contour points with small… 

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