2012.07.01-,南京理工大学计算机科学与工程学院
2010.10-2011.10,悉尼大学,医学影像分析,联合培养博士生
2009.10-2010.5,中科院深圳先进技术研究院,医学影像分析,客座学生

1. 2007年－2012年，南京理工大学，计算机科学与工程学院，博士，导师：孙权森
2. 2003年－2007年，南京理工大学，计算机科学与工程学院，学士

(1) 纪则轩(#)，孙权森(*)（1/2），基于模糊聚类的脑磁共振图像分割技术研究，江苏省教育厅，2013年江苏省优秀博士论文，2013.05.22（指导教师：孙权森）
(2) 李冠男(#)，纪则轩(*)（2/2），基于改进型高斯混合模型的脑MR图像分割技术研究，江苏省本专科毕业设计评优与抽检组织工作委员会，2014年江苏省普通高等学校本专科优秀毕业设计二等奖，2015.04.01 （指导教师：纪则轩）
(3) Zexuan Ji(#)(*), Jinyao Liu, Hengdong Yuan, Yubo Huang, Quansen Sun. A Spatially Constrained Asymmetric Gaussian Mixture Model for Image Segmentation. 7th Pacific Rim Symposium on Image and Video Technology. 2015. IAPR Best Paper.

江苏省人工智能学会组织工作委员会副主任
IEEE会员，中国计算机学会会员
十余个学术期刊审稿人：
IEEE Transactions on Image Processing、IEEE Transactions on Medical Imaging、IEEE Transactions on Cybernetics、IEEE Transactions on Biomedical Engineering、IEEE Transactions on Fuzzy Systems、Information Sciences等

(1) 江苏省自然科学基金（青年基金项目），基于变分混合模型的脑磁共振图像分割及病变检测，BK20140790，2014.7-2017.6，20万，已结题，主持
(2) 国家自然科学基金项目（青年科学基金项目），基于变分贝叶斯模型的脑磁共振图像组织分割及病变检测，61401209，2015.1-2017.12，24万，已结题，主持
(3) 中国博士后科学基金第七批特别资助，基于模糊统计模型的脑磁共振图像组织分割及病变检测，2014T70525，2014.7-2016.6，15万，已结题，主持
(4) 中国博士后科学基金面上项目（第53批），模糊活动轮廓模型的脑磁共振图像分割理论及应用研究，2013M531364，2013.7-2015.12，5万，已结题，主持
(5) 中央高校基本科研业务费专项资金资助，基于非对称有限混合模型的图像分割算法研究，30916011324，2016.1-2017.12，10万，待结题，主持
(6) 南京理工大学“卓越计划‘紫金之星’”人才计划，2014.1-2016.12，13万，已结题，主持

[1]      Zexuan Ji, Qiang Chen, Menglin Wu, Sijie Niu, Wen Fan, Songtao Yuan, Quansen Sun. Beyond Retinal Layers: A Large Blob Detection for Subretinal Fluid Segmentation in SD-OCT Images. MICCAI 2018. 录用带发表.

[2]      Zexuan Ji, Qiang Chen, Sijie Niu, Theodore Leng, Daniel L. Rubin. Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images. Translational Vision Science and Technology. 2018 Jan; 7(1): 1. (SCI, JCR3, IF: 2.221)

[3]      Tao Wang, Quansen Sun, Qi Ge, Zexuan Ji*, Qiang Chen, Guiyu Xia. Interactive Image Segmentation via Pairwise Likelihood Learning. Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, IJCAI 2017, pp. 2957-2963. (CCF A类会议)

[4]      Zexuan Ji, Yubo Huang, Yong Xia, Yuhui Zheng. A robust modified Gaussian mixture model with rough set for image segmentation. Neurocomputing. 2017, 266, 550-565 (SCI, JCR2, IF: 3.317).

[5]      Zexuan Ji, Yong Xia, Yuhui Zheng. Robust generative asymmetric GMM for brain MR image segmentation. Computer Methods and Programs in Biomedicine, 2017, 151, 123-138 (SCI, JCR2, IF: 2.503)

[6]      Zexuan Ji, Yubo Huang, Quansen Sun, Guo Cao, Yuhui Zheng. A Rough Set Bounded Spatially Constrained Asymmetric Gaussian Mixture Model for Image Segmentation. PLoS ONE, 2017, 12(1): e0168449 (SCI, JCR3, IF: 2.806)

[7]      Yantao Song, Zexuan Ji*, Quansen Sun, Yuhui Zheng. A Novel Brain Tumor Segmentation from Multi-Modality MRI via A Level-Set-Based Model. Journal of Signal Processing Systems. 2017, 87(2), 249-257. (SCI, JCR4, IF: 0.893)

[8]      Zexuan Ji, Yubo Huang, Quansen Sun, Guo Cao. A spatially constrained generative asymmetric Gaussian mixture model for image segmentation. Journal of Visual Communication and Image Representation. 2016, 40, 611-626 (SCI, JCR3, IF: 2.164)

[9]      Tao Wang, Zexuan Ji*, Quansen Sun, Qiang Chen, Xiaoyuan Jing. Interactive multi-label image segmentation via robust multi-layer graph constraints. IEEE Transactions on Multimedia, 2016, 18(12), 2358-2371. (SCI, JCR1 Top期刊, IF: 3.509)

[10]  Tao Wang, Quansen Sun, Zexuan Ji*, Qiang Chen, Peng Fu. Multi-layer graph constraints for interactive image segmentation via game theory. Pattern Recognition, 2016, 55(C):28-44. (SCI, JCR2, IF: 4.582)

[11]  Yong Xia, Zexuan Ji*, Yanning Zhang. Brain MRI image segmentation based on learning local variational Gaussian mixture models. Neurocomputing. 2016, 204: 189-197 (SCI, JCR2, IF: 3.317)

[12]  Zexuan Ji, Yong Xia, Quansen Sun, Guo Cao, Qiang Chen. Active Contours Driven by Local Likelihood Image Fitting Energy for Image Segmentation. Information Sciences. 2015, 301: 285-304 (SCI, JCR1 Top期刊, IF: 4.832) [Google Scholar引用25次，Web of Science引用21次]

[13]  Zexuan Ji, Yong Xia, Quansen Sun, Guo Cao. Interval-valued Possibilistic Fuzzy C-Means Clustering Algorithm. Fuzzy Sets and Systems. 2014. 253(16): 138-156. (SCI, JCR1 Top期刊, IF: 2.718). [Google Scholar引用42次，Web of Science引用23次]

[14]  Zexuan Ji, Jinyao Liu, Guo Cao, Quansen Sun, Qiang Chen. Robust Spatially Constrained Fuzzy C-Means Algorithm for Brain MR Image Segmentation. Pattern Recognition. 2014. 47(7): 2454-2466. (SCI, JCR2, IF: 4.582) [Google Scholar引用58次，Web of Science引用37次]

[15]  Zexuan Ji, Yong Xia, Quansen Sun, Qiang Chen, Dagan Feng. Adaptive Scale Fuzzy Local Gaussian Mixture Model for Brain MR Image Segmentation. Neurocomputing. 2014. 134: 60-69. (SCI, JCR2, IF: 3.317) [Google Scholar引用29次，Web of Science引用18次].

[16]  Zexuan Ji, Yong Xia, Quansen Sun, Qiang Chen, Deshen Xia, David Dagan Feng. Fuzzy Local Gaussian Mixture Model for brain MR image segmentation. IEEE Transactions on Information Technology in BioMedicine. 2012, 16(3): 339-347. (SCI, JCR2, IF: 1.978) [Google Scholar引用75次，Web of Science引用46次]

[17]  Zexuan Ji, Yong Xia, Quansen Sun, Qiang Chen, Deshen Xia, David Dagan Feng. Fuzzy C-Means Clustering with Weighted Image Patch for Image Segmentation. Applied Soft Computing. 2012, 12(6): 1659-1667. (SCI, JCR2, IF: 3.541) [Google Scholar引用76次，Web of Science引用42次]

[18]  Zexuan Ji, Quansen Sun, Yong Xia, Qiang Chen, Deshen Xia, Dagan Feng. Generalized Rough Fuzzy C-Means Algorithm for Brain MR Image Segmentation. Computer Methods and Programs in Biomedicine. 2012, 108(2): 644-655. (SCI, JCR2, IF: 2.503) [Google Scholar引用54次，Web of Science引用26次]

[19]  Zexuan Ji, Quansen Sun, Deshen Xia. A Modified Possibilistic Fuzzy c-means Clustering algorithm for Bias Field Estimation and Segmentation of Brain MR Image. Computerized Medical Imaging and Graphics. 2011, 35(5): 383-97. (SCI, JCR4, IF: 1.738). [Google Scholar引用114次，Web of Science引用50次]

[20]  Zexuan Ji, Qiang Chen, Quansen Sun, Deshen Xia. A moment-based nonlocal-means algorithm for image denoising. Information Processing Letters. 2009, 109: 1238-1244. (SCI, JCR4, IF: 0.748) [Google Scholar引用91次，Web of Science引用42次]

1、遥感图像的多角度自动MTF估计方法,CN 104537646 B.,南京理工大学,纪则轩,孙权森,刘金尧,贾惠珍,査艺易,赵家成,王明良,发明专利,授权
2、基于深度投票模型的SD-OCT图像GA病变分割方法,201710793834.6,南京理工大学,纪则轩,陈强,发明专利,申请
3、基于多模态磁共振的脑肿瘤图像分割方法,201710812864.7,南京理工大学,纪则轩,发明专利,申请
4、基于互斥性标签K-SVD及多尺度稀疏的高光谱图像分类方法,201711454166.0,南京理工大学,纪则轩,谢梦蓝,孙权森,发明专利,申请
5、基于结构相似性快速鲁棒的可见光与SAR图像配准方法,201711447954.7,南京理工大学,纪则轩,秦杰,孙权森,发明专利,申请

1、数字信号处理研究,研究生,7,32
2、计算机仿真,本专科生,67,32
3、OFFICE高级应用,本专科生,40,96
4、Matlab编程,本专科生,29,32
5、C语言程序设计,本专科生,102,64
6、Visual C++课程设计,本专科生,92,16
7、Visual C++程序设计,本专科生,88,64
8、C语言课程设计,本专科生,87,16
9、Pattern Recognition Technology,研究生,7,32

指导硕士研究生8人，其中4人已毕业；

协助指导博士研究生3人，其中2人已毕业。

研究方向包括：

医学影像分析（脑磁共振图像和人眼OCT图像）

模式识别理论（稀疏表示、子空间聚类、字典学习）

深度学习

遥感数据处理

图像质量评价