一、近年代表性论文: 1.Zhe Liu, Yu-Qing Song, Victor S. Sheng, Liangmin Wang, Rui Jiang, Xiaolin Zhang, Deqi Yuan, Liver CT sequence segmentation based with improved U-Net and graph cut. Expert Syst. Appl. 126: 54-63 (2019) 2.Zhe Liu, Yuqing Song, Victor S. Sheng, Chunyan Xu, Charlie Maere, Kaifeng Xue, Kai Yang,MRI and PET Image Fusion Using the Nonparametric Density Model and the Theory of Variable-Weight, Comput. Methods Programs Biomed. ,175: 73-82 (2019) 3.Zhe Liu, Cheng-Jian Qiu, Yu-Qing Song, Xiaohong Liu, Juan Wang, Victor S. Sheng,Texture Feature Extraction from Thyroid MR Imaging Using High-Order Derived Mean CLBP,J. Comput. Sci. Technol. 34(1): ,34(1): 35-46 (2019) 4.Zhe Liu, Bao Xiang, Yuqing Song, Hu Lu, Qingfeng Liu,An Improved Unsupervised Image Segmentation Method Based on Multi-Objective Particle Swarm Optimization Clustering Algorithm,Computers, Materials & Continua,58(2):451-461,(2019) 5.Zhao-Hui Wang, Zhe Liu*, Yu-Qing Song, Yan Zhu,Densely connected deep U-Net for abdominal multi-organ segmentation. ICIP 2019: 1415-1419 6.Peng Chen, Yuqing Song, Zhe Liu ,Deqi Yuan,Feature fusion adversarial learning network for liver lesion classification. MMAsia 2019: 21:1-21:7 7.Xu Yao, Yuqing Song, Zhe Liu,Advances on pancreas segmentation: a review. Multim. Tools Appl. 79(9-10): 6799-6821 (2020) 8.Thomas M. Epalle , Yuqing Song, Hu Lu, Zhe Liu,Characterizing and Identifying Autism Disorder Using Regional Connectivity Patterns and Extreme Gradient Boosting Classifier.ICONIP (4) 2019: 570-579 9.Zhe Liu, Yuqing Song, Charlie Maere, Qingfeng Liu, Yan Zhu, Hu Lu, Deqi Yuan,A Method for PET-CT Lung Cancer Segmentation based on Improved Random Walk,ICPR,2018 10.Zhe Liu,Yu-qing Song,Cong-hua Xie,Zheng Tang,A new clustering method of gene expression data based on multivariate Gaussian mixture models,Signal, Image and Video Processing,10, pages359–368(2016) 11.Zhe Liu, Yuqing Song, Zheng Tang,Noised image segmentation based on rough set and orthogonal polynomial density model. J. Electronic Imaging 24(2): 023010 (2015) 12.Yuqing Song, Xiang Bao, Zhe Liu, Deqi Yuan, Minshan Song:An Improved Brain MRI Segmentation Method Based on Scale-Space Theory and Expectation Maximization Algorithm. PCM (2) 2015: 516-525lynomial density model. J. Electronic Imaging 24(2): 023010 (2015) 13.宋余庆; 谢熹; 刘哲; 邹小波,基于多层特征融合的农作物病虫害识别方法,农业机械学报,2020.5 14.刘哲; 邹小波; 宋余庆; 王明; 苏骏,基于多特征融合和水平集的碧根果品质检测,农业机械学报,2019.11 15.刘哲; 徐涛; 宋余庆; 徐春艳,基于NSCT变换和相似信息鲁棒主成分分析模型的图像融合技术,吉林大学学报(工学版),2018.9 16.刘哲; 张晓林; 宋余庆; 朱彦; 袁德琪结合改进的U-Net和Morphsnakes肝脏分割,中国图象图形学报,2018.8 17.刘庆烽; 刘哲; 宋余庆; 朱彦,于约束随机游走的肿瘤图像分割方法. 计算机科学, 2018.7 18.刘哲,宋余庆,王栋栋自适应变异差分算法与Powell算法相结合的医学图像配准 . 计算机科学, 2017.11 二、已授权/申请的发明专利: 一种医学图像分割方法(ZL201610986747.8 ) 一种医学图像聚类方法(ZL201310209709.8) 一种XML文档到数据库的映射方法(ZL201010527890.3) 一种嵌入式设备与远程数据库进行数据交换的方法(ZL201010214154.2) 一种基于视频的行为识别方法(CN201910831903.7) 一种压缩传感图像重构方法(CN201510336805.8) 一种医学图像融合方法(CN201611173999.5) 一种医学图像配准方法(CN201611174000.9) 三、在研/已结题的项目: 1. 国家自然科学基金青年项目,基于非参数密度模型和粗糙集的多模态医学图像处理关键技术fb体育研究,2015.01-2017.12 2. 江苏省自然科学基金,粗糙集和非参数正交多项式模型病理学图像处理fb体育研究,2013.07-2016.06 3. 国家自然科学基金面上项目,并行架构下基于深度迁移学习的多种模态胰腺肿瘤图像的早期诊断与分析,2018.01-2021.12 4. 中国博士后面上项目,基于图像识别的碧根果品质无损检测fb体育研究,2017.05-2020.01 5. 国家自然科学基金面上项目,基于多目标优化和栈式稀疏编码的肝脏肿瘤图像识别fb体育研究,2016.01-2019.12 6. 国家自然科学基金面上项目,多组学特征融合的肝癌智能分期分型fb体育研究,2020.01-2023.12 7. 江苏省六大人才高峰高层次人才,2019.01-2021.01 8. 江苏高校“青蓝工程”培养对象,2017.06-2020.06 四、近年来的获奖情况: 1. 中国公路学会科技进步一等奖(提名国家奖),排名第一,2018 2. 中国商业联合会中国商业科技进步一等奖,排名第二(校内第一),2017 3. 江苏省科技进步三等奖,排名第三,2019. |