publications

2022

1. 

   X-ray dissectography enables stereotography

   Niu, Chuang, and Wang, Ge

   In 7th International Conference on Image Formation in X-Ray Computed Tomography 2022

   Bib

   @inproceedings{niu2022x,
     title = {X-ray dissectography enables stereotography},
     author = {Niu, Chuang and Wang, Ge},
     booktitle = {7th International Conference on Image Formation in X-Ray Computed Tomography},
     volume = {12304},
     pages = {396--401},
     year = {2022},
     organization = {SPIE},
     bibtex_show = {true},
     preview = {stereo.gif}
   }

2. 

   Unsupervised contrastive learning based transformer for lung nodule detection

   Niu, Chuang, and Wang, Ge

   Physics in Medicine & Biology Oct 2022

   Bib

   @article{Niu_2022,
     doi = {10.1088/1361-6560/ac92ba},
     url = {https://dx.doi.org/10.1088/1361-6560/ac92ba},
     year = {2022},
     month = oct,
     publisher = {IOP Publishing},
     volume = {67},
     number = {20},
     pages = {204001},
     author = {Niu, Chuang and Wang, Ge},
     title = {Unsupervised contrastive learning based transformer for lung nodule detection},
     journal = {Physics in Medicine & Biology},
     bibtex_show = {true},
     preview = {trans.png}
   }

3. 

   Self-supervised dual-domain network for low-dose CT denoising

   Niu, Chuang, Li, Mengzhou, Guo, Xiaodong, and Wang, Ge

   In Proc. of SPIE Vol 2022

   Bib

   @inproceedings{niu2022self,
     title = {Self-supervised dual-domain network for low-dose CT denoising},
     author = {Niu, Chuang and Li, Mengzhou and Guo, Xiaodong and Wang, Ge},
     booktitle = {Proc. of SPIE Vol},
     volume = {12242},
     pages = {122420H--1},
     bibtex_show = {true},
     year = {2022},
     preview = {dual_ldct.png}
   }

4. 

   Multi-view x-ray dissectography improves nodule detection

   Niu, Chuang, Dasegowda, Giridhar, Yan, Pingkun, Kalra, Mannudeep K., and Wang, Ge

   In Developments in X-Ray Tomography XIV 2022

   Bib

   @inproceedings{10.1117/12.2637782,
     author = {Niu, Chuang and Dasegowda, Giridhar and Yan, Pingkun and Kalra, Mannudeep K. and Wang, Ge},
     title = {{Multi-view x-ray dissectography improves nodule detection}},
     volume = {12242},
     booktitle = {Developments in X-Ray Tomography XIV},
     editor = {M{\"u}ller, Bert and Wang, Ge},
     organization = {International Society for Optics and Photonics},
     publisher = {SPIE},
     pages = {1224217},
     keywords = {Lung nodule detection, x-ray imaging},
     year = {2022},
     doi = {10.1117/12.2637782},
     url = {https://doi.org/10.1117/12.2637782},
     bibtex_show = {true},
     preview = {multi_view.png}
   }

5. 

   Home: high-order mixed-moment-based embedding for representation learning

   Niu, Chuang, and Wang, Ge

   arXiv preprint arXiv:2207.07743 2022

   Bib

   @article{niu2022home,
     title = {Home: high-order mixed-moment-based embedding for representation learning},
     author = {Niu, Chuang and Wang, Ge},
     journal = {arXiv preprint arXiv:2207.07743},
     year = {2022},
     bibtex_show = {true},
     preview = {home.png}
   }

6. 

   Self-supervised representation learning with MUlti-Segmental Informational Coding (MUSIC)

   Niu, Chuang, and Wang, Ge

   arXiv preprint arXiv:2206.06461 2022

   Bib

   @article{niu2022music,
     title = {Self-supervised representation learning with {MU}lti-{S}egmental {I}nformational {C}oding ({MUSIC})},
     author = {Niu, Chuang and Wang, Ge},
     journal = {arXiv preprint arXiv:2206.06461},
     year = {2022},
     bibtex_show = {true},
     selected = {true},
     preview = {music.png}
   }

2021

1. 

   SPICE: Semantic Pseudo-labeling for Image Clustering

   Niu, Chuang, Shan, Hongming, and Wang, Ge

   arXiv preprint arXiv:2103.09382 (Accepted by TIP) 2021

   Bib Code

   @article{niu2021spice,
     title = {{SPICE}: Semantic {P}seudo-labeling for {I}mage {C}lustering},
     author = {Niu, Chuang and Shan, Hongming and Wang, Ge},
     journal = {arXiv preprint arXiv:2103.09382 (Accepted by TIP)},
     year = {2021},
     bibtex_show = {true},
     preview = {spice.png},
     code = {https://github.com/niuchuangnn/SPICE},
     selected = {true}
   }

2. 

   Low-dimensional manifold constrained disentanglement network for metal artifact reduction

   Niu, Chuang, Cong, Wenxiang, Fan, Feng-Lei, Shan, Hongming, Li, Mengzhou, Liang, Jimin, and Wang, Ge

   IEEE Transactions on Radiation and Plasma Medical Sciences 2021

   Bib

   @article{niu2021low,
     title = {Low-dimensional manifold constrained disentanglement network for metal artifact reduction},
     author = {Niu, Chuang and Cong, Wenxiang and Fan, Feng-Lei and Shan, Hongming and Li, Mengzhou and Liang, Jimin and Wang, Ge},
     journal = {IEEE Transactions on Radiation and Plasma Medical Sciences},
     year = {2021},
     publisher = {IEEE},
     bibtex_show = {true},
     preview = {ldm.png}
   }

3. 

   Multiple window learning for CT metal artifact reduction

   Niu, Chuang, Li, Mengzhou, and Wang, Ge

   In Developments in X-Ray Tomography XIII 2021

   Bib

   @inproceedings{niu2021multiple,
     title = {Multiple window learning for CT metal artifact reduction},
     author = {Niu, Chuang and Li, Mengzhou and Wang, Ge},
     booktitle = {Developments in X-Ray Tomography XIII},
     volume = {11840},
     pages = {161},
     year = {2021},
     organization = {SPIE},
     bibtex_show = {true},
     preview = {mwnet.png}
   }

4. 

   Noise entangled GAN for low-dose CT simulation

   Niu, Chuang, Wang, Ge, Yan, Pingkun, Hahn, Juergen, Lai, Youfang, Jia, Xun, Krishna, Arjun, Mueller, Klaus, Badal, Andreu, Myers, KyleJ, and others,

   arXiv preprint arXiv:2102.09615 2021

   Bib

   @article{niu2021noise,
     title = {Noise entangled GAN for low-dose CT simulation},
     author = {Niu, Chuang and Wang, Ge and Yan, Pingkun and Hahn, Juergen and Lai, Youfang and Jia, Xun and Krishna, Arjun and Mueller, Klaus and Badal, Andreu and Myers, KyleJ and others},
     journal = {arXiv preprint arXiv:2102.09615},
     year = {2021},
     bibtex_show = {true},
     preview = {negan.png}
   }

2020

1. 

   GATCluster: Self-supervised Gaussian-ATtention network for image Clustering

   Niu, Chuang, Zhang, Jun, Wang, Ge, and Liang, Jimin

   In European Conference on Computer Vision 2020

   Bib Code

   @inproceedings{niu2020gatcluster,
     title = {{GATC}luster: Self-supervised {G}aussian-{AT}tention network for image {C}lustering},
     author = {Niu, Chuang and Zhang, Jun and Wang, Ge and Liang, Jimin},
     booktitle = {European Conference on Computer Vision},
     pages = {735--751},
     year = {2020},
     organization = {Springer},
     bibtex_show = {true},
     preview = {gatcluster.jpg},
     code = {https://github.com/niuchuangnn/GATCluster},
     selected = {true}
   }

2. 

   Noise2sim–similarity-based self-learning for image denoising

   Niu, Chuang, and Wang, Ge

   arXiv preprint arXiv:2011.03384 (Accepted by TMI) 2020

   Bib Code

   @article{niu2020noise2sim,
     title = {Noise2sim--similarity-based self-learning for image denoising},
     author = {Niu, Chuang and Wang, Ge},
     journal = {arXiv preprint arXiv:2011.03384 (Accepted by TMI)},
     year = {2020},
     bibtex_show = {true},
     preview = {noise2sim.png},
     code = {https://github.com/niuchuangnn/noise2sim},
     selected = {true}
   }

2019

1. 

   Joint Classification and Instance Segmentation of Auroral Images for Automatic Computation of Arc Width

   Niu, Chuang, Tang, Yiping, Ren, Shenghan, Hu, Ze-Jun, Desheng, Han, and Liang, Jimin

   In AGU Fall Meeting Abstracts 2019

   Bib

   @inproceedings{niu2019joint,
     title = {Joint Classification and Instance Segmentation of Auroral Images for Automatic Computation of Arc Width},
     author = {Niu, Chuang and Tang, Yiping and Ren, Shenghan and Hu, Ze-Jun and Desheng, Han and Liang, Jimin},
     booktitle = {AGU Fall Meeting Abstracts},
     volume = {2019},
     pages = {NG31A--0854},
     year = {2019},
     bibtex_show = {true},
     preview = {arc.png}
   }

2. 

   Instance segmentation of auroral images for automatic computation of arc width

   Niu, Chuang, Yang, Qiuju, Ren, Shenghan, Hu, Haihong, Han, Desheng, Hu, Ze-Jun, and Liang, Jimin

   IEEE Geoscience and Remote Sensing Letters 2019

   Bib Code

   @article{niu2019instance,
     title = {Instance segmentation of auroral images for automatic computation of arc width},
     author = {Niu, Chuang and Yang, Qiuju and Ren, Shenghan and Hu, Haihong and Han, Desheng and Hu, Ze-Jun and Liang, Jimin},
     journal = {IEEE Geoscience and Remote Sensing Letters},
     volume = {16},
     number = {9},
     pages = {1368--1372},
     year = {2019},
     publisher = {IEEE},
     bibtex_show = {true},
     preview = {instance.jpg},
     code = {https://github.com/niuchuangnn/aurora-maskrcnn}
   }

2018

1. 

   Weakly-and Semi-Supervised Semantic Segmentation for Aurora Image Classification

   Niu, Chuang, Ren, Shenghan, Hu, Haihong, Desheng, Han, Hu, Zejun, and Liang, Jimin

   In AGU Fall Meeting 2018 2018

   Bib

   @inproceedings{niu2018weakly,
     title = {Weakly-and Semi-Supervised Semantic Segmentation for Aurora Image Classification},
     author = {Niu, Chuang and Ren, Shenghan and Hu, Haihong and Desheng, Han and Hu, Zejun and Liang, Jimin},
     booktitle = {AGU Fall Meeting 2018},
     year = {2018},
     organization = {AGU},
     bibtex_show = {true},
     preview = {joint.png}
   }

2. 

   Weakly supervised semantic segmentation for joint key local structure localization and classification of aurora image

   Niu, Chuang, Zhang, Jun, Wang, Qian, and Liang, Jimin

   IEEE Transactions on Geoscience and Remote Sensing 2018

   Bib Code

   @article{niu2018weaklz,
     title = {Weakly supervised semantic segmentation for joint key local structure localization and classification of aurora image},
     author = {Niu, Chuang and Zhang, Jun and Wang, Qian and Liang, Jimin},
     journal = {IEEE Transactions on Geoscience and Remote Sensing},
     volume = {56},
     number = {12},
     pages = {7133--7146},
     year = {2018},
     publisher = {IEEE},
     bibtex_show = {true},
     preview = {weakly.jpg},
     code = {https://github.com/niuchuangnn/Aurora-ASI-KLS},
     selected = {true}
   }