DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy

@inproceedings{He2019DPADenseBiasNetS3,
  title={DPA-DenseBiasNet: Semi-supervised 3D Fine Renal Artery Segmentation with Dense Biased Network and Deep Priori Anatomy},
  author={Yuting He and Guanyu Yang and Yang Chen and Youyong Kong and Jiasong Wu and L. Tang and Xiaomei Zhu and J. Dillenseger and P. Shao and Shaobo Zhang and H. Shu and J. Coatrieux and S. Li},
  booktitle={MICCAI},
  year={2019}
}
3D fine renal artery segmentation on abdominal CTA image targets on the segmentation of the complete renal artery tree which will help clinicians locate the interlobar artery’s corresponding blood feeding region easily. However, it is still a challenging task that no one has reported success due to the large intra-scale changes, large inter-anatomy variation, thin structures, small volume ratio and limitation of labeled data. Hence, in this paper, we propose a novel semi-supervised learning… Expand
Meta grayscale adaptive network for 3D integrated renal structures segmentation
  • Yuting He, Guanyu Yang, +9 authors Shuo Li
  • Computer Science, Medicine
  • Medical Image Anal.
  • 2021
EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
Medical Image Segmentation With Limited Supervision: A Review of Deep Network Models
Recent advances and clinical applications of deep learning in medical image analysis
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