智能医学影像分析与精准诊断团队

发布时间: 2020-12-27?| ?查看数:3481

团队名称:智能医学影像分析与精准诊断团队

 

主要研究领域:

– 智能医学成像(快速MRI,低剂量CT,微观成像)

– 医学图像处理(医学图像分割、配准、融合、去噪、超分辨率重建)

– 人工智能辅助诊断(肿瘤分期分型、肿瘤预后预测、神经系统疾病分类)

 

团队负责人:王丽会,教授,博士,博导、硕导

主要团队成员

王荣品       教授,博士,硕导(医学院博导)

曾宪春       教授,博士,博导、硕导

YueMin ZHU,教授,博士,博导(外聘,仅招博士)

程欣宇       副教授,硕导

张   健       副教授,博士,硕导

叶   晨       副教授,博士,硕导

喻   莎       副教授,博士,硕导

陶   熙       副教授,博士,硕导

林莉燕       副教授,博士,硕导

陈   怡       助理实验师,在读博士

 

部分论文(2019-2024

[1] Hu, Xubin, Lihui Wang*, Li Wang, Qijian Chen, Licheng Zheng, and YueMin Zhu. Glioma segmentation based on dense contrastive learning and multimodal features recalibration. Physics in Medicine and Biology (2024)

[2] He J, Zhang M, Li W, Rongpin WANG* et al. SaB-Net: Self-attention backward network for gastric tumor segmentation in CT images[J]. Computers in Biology and Medicine, 2024, 169: 107866.中科院二区Top

[3] Chen, Q, Wang, L*., Xing, Z., Wang, L., Hu, X., Wang, R., & Zhu, Y. M. (2023). Deep wavelet scattering orthogonal fusion network for glioma IDH mutation status prediction. Computers in Biology and Medicine, 166, 107493. (中科院二区Top)

[4] Junjie He, Yunsong Peng, Bangkang Fu, Yuemin Zhu, Lihui Wang, Rongpin Wang*, msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping, NeuroImage, Volume 275, 2023, 120181, ISSN 1053-8119 .(中科院top)

[5] Tang, Kun, Lihui Wang*, Xingyu Huang, Xinyu Cheng, and Yue-Min Zhu. MD-SGT: Multi-dilation spherical graph transformer for unsupervised medical image registration. Computerized Medical Imaging and Graphics 108 (2023): 102281.(中科院二区)

[6] Yuan N, Wang L*, Ye C, Jian Zhang et al. Self-supervised Structural Similarity-based Convolutional Neural Network for Cardiac Diffusion Tensor Image Denoising[J]. Medical Physics, 2023.(中科院二区)

[7] Zixuan Hong, Dong Zeng, Xi Tao*, Jianhua Ma*. Learning CT projection denoising from adjacent views. Medical Physics, 2023, 50(1367–1377). (中科院二区)

[8] Guo H, Wang L*, Gu Y, Jian ZHANG et al. Semi-supervised super-resolution of diffusion-weighted images based on multiple references[J]. NMR in Biomedicine, 2023: e4919.

[9] Sun, Xinhuan, Wuchao Li, Bangkang Fu, Yunsong Peng, Junjie He, Lihui Wang, Tongyin Yang, Xue Meng, Jin Li, Jinjing Wang, Ping Huang and Rongpin Wang*. “TGMIL: A hybrid multi-instance learning model based on the Transformer and the Graph Attention Network for whole-slide images classification of renal cell carcinoma.” Computer methods and programs in biomedicine 242 (2023): (中科院区)

[10] L. H. Wang, Y.B. Qin, F. Yang, J. Yang, and Y. M. Zhu, Connecting macroscopic diffusion metrics of cardiac diffusion tensor imaging and microscopic myocardial structures based on simulation,” Medical Image Analysis, vol. 77, April, 2022. doi.org/10.1016/j.media.2021.102325. (中科院一区Top)

[11] Xiong X, Wang L, Li Z, et al. An adaptive high-capacity reversible data hiding algorithm in interpolation domain[J]. Signal Processing, 2022, 194: 108458.(中科院二区)

[12] Y. L. Qin, Zheng, Y. Gu, X. L. Huang, J.Yang, L. H. Wang, F. Yao, Y.M. Zhu, G. Z. Yang, “Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation, IEEE Trans. on Medical Imaging, 2021.10.1109/TMI.2021.3062280. (中科院一区Top)

[13] Xi Tao, Yongbo Wang, Liyan Lin, Zixuan Hong, Jianhua Ma. Learning to reconstruct CT images from the VVBP-Tensor. IEEE Transactions on Medical Imaging, 2021, 40(11): 3030-3041.(中科院一区Top)

[14] Liyan Lin, Xi Tao, Wei Yang, Shumao Pang, Zhihai Su, Hai Lu, Shuo Li, Qianjin Feng, Bo Chen. Quantifying Axial Spine Images Using Object-Specific Bi-Path Network. IEEE Journal of Biomedical and Health Informatics, 2021, 25(8): 2978-2987. (中科院二区Top)

[15] Xinyu Cheng; Cheng bo Li; Yixue Peng; Chuang Zhao; Discrete element simulation of  super-ellipse systems, Granular Matter, 2021, 23(2): 1-14

[16] 田梨梨; 程欣宇; 唐堃; 张健; 王丽会; 集成注意力增强和双重相似性引导的多模态脑部图像配准, 中国图象图形学报, 2021, 26(9): 2219-2232.

[17] C. Ye, D. Y. Xu, Y. B. Qin, L. H. Wang, R. P. Wang, W. C. Li, Z. X. Kuai, and Y. M. Zhu, Accurate IVIM Parameter Estimation Using Bayesian Fitting and Reduced Number of Low b-Values,” Medical Physics, 2020. DOI:10.1002/mp.14233, Vol. 47, pp.4372-4385.(中科院二区)

[18] Xi Tao, Hua Zhang, Yongbo Wang, Gang Yan, Dong Zeng, Wufan Chen, Jianhua Ma. VVBP-Tensor in the FBP algorithm: Its properties and application in low-dose CT reconstruction. IEEE Transactions on Medical Imaging, 2020, 39(3): 764-776.(中科院一区Top)

[19] Sha Yu, Kevin McGuinness, Patricia Moore, David Azcona, Noel OConnor, A Smart-Site-Survey System using Image-based 3D Metric Reconstruction and Interactive Panorama Visualization, ACM Multimedia Conference (ACM MM), Seattle, United States, 12-16 October 2020. 计算机学会CCF A类,Core Ranking A*.

[20] Liyan Lin, Xi Tao, Shumao Pang, Zhihai Su, Hai Lu, Shuo Li, Qianjin Feng, Bo Chen. Multiple axial spine indices estimation via dense enhancing network with cross-space distance-preserving regularization. IEEE journal of biomedical and health informatics, 2020, 24(11): 3248-3257.(中科院二区Top)

[21] Chen Ye; Daoyun Xu; Lihui Wang; Rongpin Wang; Yuemin Zhu ; Application of machine learning in optimizing b-value acquisition strategy of diffusion Magnetic Resonance Imaging, 2020International Conference on Machine Learning and Computer Application, Shangri-La, China, 2020-9-112020-9-13

[22] Chen Ye; Daoyun Xu; Lihui Wang; Yuemin Zhu ; Application of machine learning on the modelling of diffusion Magnetic Resonance Imaging signal, The 2020 International Seminar onArtificial Intelligence, Networking and Information Technology, Shanghai, China, 2020-9-182020-9-20

[23] J. Huang, L. Wang*, J. Qin, Y. Chen, X. Cheng and Y. Zhu, Super-Resolution of Intravoxel Incoherent Motion Imaging Based on Multisimilarity, IEEE Sensors Journal, 2019, vol. 20, no. 18, pp. 10963-10973. (SCI)(中科院二区Top)

[24] Sun C, Tian X, Liu Z, Li W, Li P, Chen J*, Zhang W, Fang Z, Du P, Duan H, Liu P, Wang L*, Chen C, Tian J*. Radiomic analysis for pretreatment prediction of response to neoadjuvant chemotherapy in locally advanced cervical cancer: A multicentre study. EBioMedicine. 2019, 46:160-169. (SCI) (中科院一区Top)

[25] Sha Yu, Yao Lu, and Derek Molloy. A Dynamic-Shape-Prior Guided Snake Model with Application in Visually Tracking Dense Cell populations. IEEE Transactions on Image Processing 28.3 (2019): 1513-1527.(中科院一区Top).

[26] Chen Ye; Daoyun Xu; Yongbin Qin; Lihui Wang; Rongpin Wang; Wuchao Li; Zixiang Kuai; Yuemin Zhu; Estimation of intravoxel incoherent motion parameters using low b-values, Plos One,2019, 14(2): 1-16.

 

部分研究课题

[1] 国家自然科学基金地区项目,面向细胞群跟踪的深度活动网模型及跨域自适应性算法研究,2024.01-2027.12,主持人,喻莎。

[2] 国家自然科学基金地区项目,基于深度学习的药物成瘾神经机制及影像标记研究,2022.01-2025.12,主持人,王丽会。

[3] 国家自然科学基金地区项目,基于影像-病理多尺度模型智能预测肾透明细胞癌术后预后研究,2022.01-2025.12,主持人,王荣品。

[4] 国家自然科学基金青年项目,62101238,基于反投影张量建模的稀疏角度CT优质成像算法研究,2022.01-2024.12,主持人:陶熙。

[5] 国家自然科学基金青年项目,62101237,基于MRI影像的脊柱脊髓脊旁肌多类型指标自动估计新方法研究,2022.01-2024.12,主持人:林莉燕。

[6] 国家自然科学基金地区项目,影像组学联合病理组学预测进展期胃癌术后预后的研究,2020.01-2023.12,主持人,王荣品。

[7] 国家自然科学基金地区项目,基于无线整合型MRI放大器高分辨率成像探索肾小球疾病早期诊断的实验研究,2021.01-2024.12,主持人,曾宪春。

[8] 国家自然科学基金地区项目,基于云平台的多模态心肌纤维磁共振扩散成像建模与仿真算法研究,2017.01-2020.12,主持人,王丽会。

[9] 贵州省科技支撑计划,智慧戒毒关键技术与应用研究,2023.05-2025.05,主持人,王丽会。

[10] 贵州省基础研究自然科学项目,体素内不相干运动成像参数估计方法的研究,2023.01-2025.12,主持人,叶晨。

[11] 科技部外国专家项目,基于深度学习正则与非凸优化模型的医学图像重建算法研究,2022.01-2023.12,主持人,王丽会。

[12] 贵州省科学技术基金项目,基于深度学习的药物成瘾多模态脑图谱构建算法研究,2022.01-2024.12,主持人,程欣宇。

[13] 贵州省科学技术基金重点项目,基于多模态深度学习影像组学的药物成瘾神经机制研究,2021.01-2024.12,主持人,王丽会。

[14] 贵州省科学技术基金,基于深度学习的远程医疗图像压缩感知算法研究,2020.1—2022.12,主持人,张健。

[15] 中法蔡元培项目,Deep learning for realistic simulation of dynamic in vivo DTI of the human heart2018.8-2021.8,主持人,王丽会。

[16] 贵州省智能人机交互工程技术研究中心,贵州省科技平台项目,2018.8-2020.12,主持人,程欣宇。

 


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