Create README.md

README.md

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+---
+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](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8837609/) by Zheng et al. and first released in [this repository](https://github.com/no-saint-no-angel/BianqueNet). 
+
+> 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
+
+```bibtex
+@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},
+}
+```