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医学影像处理与分析实验室

地  址:苏州市姑苏区干将东路333号
邮  箱:xjchen@suda.edu.cn
邮  编:215000
 

科研成果

2019

期刊论文

1. Baoqing Nie, Rong Huang, Ting Yao, Yiqiu Zhang, Yihui Miao, Changrong Liu, Jian Liu*, Xinjian Chen*. Textile-based Wireless Pressure Sensor Array for Human-interactive Sensing. 2019.Advanced Functional Materials.[PDF]

2. Jiang H, Chen X, Shi F, Ma Y, Xiang D, Ye L, Su J, Li Z, Chen Q, Hua Y, Xu X, Zhu W*, Fan Y*. Improved cGAN based linear lesion segmentation in high myopia ICGA images[J]. Biomedical Optics Express, 2019, 10(5): 2355-2366. [PDF]

3. Geng Chen, Dehui Xiang , Bin Zhang, Haihong Tian , Xiaoling Yang, Fei Shi , Weifang Zhu, Bei Tian, and Xinjian Chen. Automatic Pathological Lung Segmentation in Low-Dose CT Image Using Eigenspace Sparse Shape Composition.IEEE transactions on Medical Imaging. DOI:10.1109/TMI.2018.2890510 [PDF]

4. Dehui Xiang, Geng Chen, Fei Shi, Weifang Zhu, Qinghuai Liu, Songtao Yuan, Xinjian Chen. Automatic retinal layer segmentation of OCT images with central serous retinopathy[J]. IEEE journal of biomedical and health informatics, 2019, 23(1): 283-295. [PDF]

5. Tang X, Miao Y, Chen X, et al. A Flexible and Highly Sensitive Inductive Pressure Sensor Array Based on Ferrite Films[J]. Sensors, 2019, 19(10): 2406. [PDF]

6. Shi F, Cai N, Gu Y, et al. DeSpecNet: a CNN-based method for speckle reduction in retinal optical coherence tomography images[J]. Physics in Medicine & Biology, 2019.[PDF]

7. Rong Y, Xiang D, Zhu W, et al. Deriving external forces via convolutional neural networks for biomedical image segmentation[J]. Biomedical Optics Express, 2019, 10(8): 3800-3814.[PDF]

8. T. Peng, Y. Wang, T. C. Xu and X. Chen, "Segmentation of Lung in Chest Radiographs Using Hull and Closed Polygonal Line Method," in IEEE Access, vol. 7, pp. 137794-137810, 2019. doi: 10.1109/ACCESS.2019.2941511.[PDF]

9. Pan, Lingjiao & Guan, Liling & Chen, Xinjian. (2019). Segmentation Guided Registration for 3D Spectral-domain Optical Coherence Tomography Images. IEEE Access. PP. 1-1. 10.1109/ACCESS.2019.2943172.[PDF]

会议论文

1. A Micro Capacitance Measurement System with Ultra-High Accuracy and Fast Speed, ISEEI/IEEE Xplore.

2. Rong Huang, Yu Zhang, Xinjian Chen*, Baoqing Nie*. A wireless flexible pressure sensor for human motion detection. CISP-BMEI.

3. Haihong Tian, Geng Chen, Deihui Xiang, and Xinjian Chen,Simultaneous and automatic two surface detection of renal cortex in 3D CT images by enhanced sparse shape composition, SPIE Medical Imaging 2019: Image Processing.

4. Xinjian Chen, et al. Automated segmentation of retinal edema lesions from OCT images using improved V-net, ARVO 2019.

5. Meng Wang, et al. Multi-strategy deep learning method for glaucoma screening on fundus image, ARVO 2019.

6. Feng S, Zhu W, Zhao H, et al. Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy[C]//International Workshop on Ophthalmic Medical Image Analysis. Springer, Cham, 2019: 139-147.

7. Yuhe Shen,?Liling Guan, Kai Yu, Xinjian Chen. A CNN based retinal regression model for Bruch’s membrane opening detection, SPIE Medical Imaging 2019: Image Processing.

8. Liling Guan, Kai Yu , Xinjian Chen. Fully automated detection and quantification of multiple retinal lesions in OCT volumes based on deep learning and improved DRLSE, SPIE Medical Imaging 2019: Image Processing.

9. Haihong Tian, Geng Chen, Deihui Xiang, Xinjian Chen. Simultaneous and automatic two surface detection of renal cortex in 3D CT images by enhanced sparse shape composition, SPIE Medical Imaging 2019: Image Processing.

专利

1. 一种无线压力传感器及其制作方法,201910091014.1,发明专利,等待实审提案,聂宝清、陈新建、黄蓉.

2. 一种无线压力传感器,201920162605.9,发明专利,已授权,聂宝清、陈新建、黄蓉.

3. 超高精度快速微电容测量系统,申请号:201910711397.8,发明专利,中通出案待答复,聂宝清、陈新建、缪一辉.

4. 一种视网膜黄斑水肿多病变图像分割方法,申请号:201910645849.7,发明专利,已授权,朱伟芳,冯爽朗,陈新建,赵鹤鸣.

5. 一种基于GCS-Net进行OCT图像脉络膜自动分割方法,申请号:201910762318.6,发明专利,已授权,石霏, 陈新建,成雪娜,朱伟芳.

6. 一种上下文金字塔融合网络及图像分割方法,申请号:201910942993.7,发明专利,一通回案实审,朱伟芳,冯爽朗,陈新建,赵鹤鸣.

专著

Chen, Xinjian, Shi, Fei, Chen, Haoyu. Retinal Optical Coherence Tomography Image Analysis. SPRINGER Verlag, SINGAPOR, 2019.


地址: 苏州市姑苏区干将东路333号   邮箱:xjchen@suda.edu.cn 
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