metadata

language:
  - en
pipeline_tag: image-segmentation
tags:
  - medical

BianqueNet

BianqueNet is a segmentation model based on DeepLabv3+ with additional modules designed to improve the segmentation accuracy with IVD-related areas from T2W MR images. It was introduced in the paper Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI by Zheng et al. and first released in this repository.

Disclaimer: This model card was not written by the team that released the BianqueNet model.

Intended uses & limitations

You can use this particular checkpoint on spine sagittal T2-weighted MRI images. See the model hub to look for other image segmentation models that might interest you.

BibTeX entry and citation info

@article{zheng2022bianquenet,
  author = {Zheng, Hua-Dong and Sun, Yue-Li and Kong, De-Wei and Yin, Meng-Chen and Chen, Jiang and Lin, Yong-Peng and Ma, Xue-Feng and Wang, Hongshen and Yuan, Guang-Jie and Yao, Min and Cui, Xue-Jun and Tian, Ying-Zhong and Wang, Yong-Jun},
  year = 2022,
  pages = 841,
  title = {Deep learning-based high-accuracy quantitation for lumbar intervertebral disc degeneration from MRI},
  volume = 13,
  journal = {Nature Communications},
}