教学/科研项目 1、国家自科基金地区基金，跨空间多模态MRI图像非对称超分辨率重建研究，2026.01 – 2029.12，33万元，主持 2、云南省应用基础研究计划面上项目，盲退化下的多对比度3D-MRI图像超分辨率研究，2025.03 – 2028.02, 10万元，主持 3、云南省应用基础研究计划青年项目，跨切片相似特征迁移MRI图像超分辨率研究，2024.03 – 2027.02, 5万元，主持 4、云南省重大科技专项子课题，多模态数据析取与全生命期数据保护关键技术研究，2024.01 –2026.12，66万元，主持 论文 [1]Lulu Wang, Siyi Liu, Zhengtao Yu, Jinglong Du,Yingna Li,Displacement-Guided Anisotropic 3D-MRI Super-Resolution with Warp Mechanism,IEEE Journal of Biomedical and Health Informatics,2026,vol. 30, no. 3, pp. 2406-2418. [2]Lulu Wang, Lang Gu, Zhengtao Yu, Jinglong Du, Yingna Li,MSDiff: Dynamic dual-attention driven multi-stage diffusion for low-dose CT image denoising,Neurocomputing, 2026,Vol 669, 7, 132456. [3]Lulu Wang,Ruiji Xue, Zhengtao Yu, Ruoyu Zhang, Tongling Pan, Yingna Li,A dynamic hybrid network with attention and mamba for image captioning,Computer Vision and Image Understanding,2026,vol. 263,104617. [4]Lulu Wang, F. Shang, J. Du, Y. Jia and Y. Li, MultiSG-Net: Integrating Multi-Source Structure Guidance and Uncertainty Perception in Medical Image Segmentation, 2025 IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 2025, pp. 4159-4164, [5]Tongling Pan,Lulu Wang, Ruoyu Zhang, Zhengtao Yu, Yingna Li;Distribution-aware network with context and entity attention for scene graph generation,Engineering Applications of Artificial Intelligence,2025,vol.160, 111984. [6]Fudong Shang; Shouguo Tang; Xiaorong Wan; Yingna Li;Lulu Wang（通讯）; BMSMM-Net: A BoneMetastasis Segmentation Framework Based on Mamba and Multiperspective Extraction, AcademicRadiology, 2025, 32(3): 1204-1217 [7]Lulu Wang, Wanqi Zhang, Wei Chen, et al.Cross-Modality Reference and Feature Mutual-Projection for 3D Brain MRI Image Super-Resolution[J],Journal of Imaging Informatics in Medicine(Journal of Digital Imaging),2024, 37: 2838-2851 [8]Lulu Wang,Huazheng Zhu, Zhongshi He, et al. Adjacent Slices Feature Transformer Network for Single Anisotropic 3D Brain MRI Image Super-Resolution[J], Biomedical Signal Processing and Control, 2022, 72:103339. [9]Lulu Wang,Jinglong Du, Ali Gholipour, et al. 3D Dense Convolutional Neural Network for Fast and Accurate Single MR Image Super-Resolution Reconstruction[J], Computerized Medical Imaging and Graphics, 2021, 93:101973. [10]Lulu Wang,Jinglong Du, Huazheng Zhu, et al. Brain MR Image Super-Resolution using 3D Feature Attention Network[C], IEEE International Conference on Bioinformatics and Biomedicine, 2020, pp.1151-1155. 专利 1、基于跨模态和跨尺度特征融合的3D磁共振超分辨率方法，发明专利，专利号：ZL202310175391.X 2、一种基于改进血细胞提取和多尺度注意的实时血细胞检测方法,发明专利，专利号：202411701780.2 3、基于偏移估计的各向异性3D-MRI超分辨率重建方法,发明专利，专利号：202510315954.X 4、基于注意力和状态空间模型的图像字幕方法,发明专利，专利号：202510433465.4 5、一种基于扩散模型的低剂量CT图像去噪泛化方法,发明专利，专利号：202510708840.1 6、基于空间熵增强的双编码器乳腺癌医学图像分割方法,发明专利，专利号：202510773920.5 7、基于相邻切片特征迁移的三维磁共振超分辨率成像方法,发明专利，专利号：202510785743.2 |
