Publications

Selected Main Conferences and Journals (# indicates co-first):

Zhao, Y., Nie, D., Chen, G., Wu, X., Zhang, D., Wen, X. TARDRL: Task-Aware Reconstruction for Dynamic Representation Learning of fMRI. MICCAI 2024 [pdf][code] (Congrats to Yunxi!)

Xue, P., Nie, D., Zhu, M., Yang, M., Zhang, H., Zhang, D., Wen, X.. WSSADN: A Weakly Supervised Spherical Age-Disentanglement Network for Detecting Developmental Disorders with Structural MRI. MICCAI 2024. [pdf][code] (Congrats to Pengcheng!)

Liu, H, Ni, Z., Nie, D., Tang, Z.. Multimodal Brain Tumor Segmentation Boosted by Monomodal Normal Brain Images. TIP 2024 [pdf][code] 

Xiao, Q., Nie, D.. Blurry Boundary Segmentation with Semantic-guided Feature Learning. MIUA 2024. [pdf][code] (Work on blurry boundary delineation)

Xiao, Q., Nie, D..  Fine-grained Medical Image Synthesis with Dual-Attention Adversarial Learning. MIUA 2024. [pdf][code] (Work on synthesis)

Wang, J., Ke, W, Nie, D, Wang, P., etal. InstructNER: Boosting Textural NER with Synthetic Image and Instructive Alignment. ACL 2024. [pdf][code] (Congrats to Jiahao!)

Lu, C., Reddy, C., Wang, P., Nie, D., Ning, Y. Multi-Label Clinical Time-Series Generation via Conditional GAN. TKDE 2023.  [pdf][code]

Liu, Y.,  Li, J.,  Pang Y., Nie, D., Yap, P.. The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior. ICCV 2023. [pdf][code] (Congrats to Yilin! Great work on understanding the essence of denoising with DIP!)

Lin, Y., Nie, D., Liu, Y., Yang, M., Zhang, D., Wen, X. Multi-Target Domain Adaptation with Prompt Learning for Medical Image Segmentation.  MICCAI 2023. [pdf][code] [local copy](Congrats to YiLi, my 2nd supervised master student)

Tang, Z., Zhang, Z., Liu, H., Gao, H., Cheng, J., Nie, D., Yang, J.. Pre-operative Survival Prediction of Diffuse Glioma Patients with Joint Tumor Subtyping. MICCAI 2023. [pdf][code][local copy] (Continuous work on tumor overall survival since our first work in 2016) 

Zhou, S.,  Nie, D., Adeli, E., Shen, D..  Semantic instance segmentation with discriminative deep supervision for medical images. MedIA 2022. [pdf][code]

Gao, L., Nie, D., Li, B., Ren, X..  DFvT: Fuse Information from  Vision Transformer Doubly with Local Representation. ECCV 2022. [pdf][code] (The first paper from my first formal intern, Proud  of Jasmine!)

Liu, H., Nie, D., Wang, J., Tang Z..  Multimodal Brain Tumor Segmentation Using Contrastive Learning based Feature Comparison with Monomodal Normal Brain Images. MICCAI 2022. [pdf] [code]

Nie, D., Lan, R., Wang, L., Ren, X.. Pyramid Architecture for Multi-Scale Processing in Point Cloud Segmentation. CVPR 2022. [pdf][code]

Huang, J., Ning, Y., Nie, D., Guan, L., Jia X.. Weakly-supervised Metric Learning with Cross-Module Communications for the Classification of Anterior Chamber Angle Images. CVPR 2022. [pdf][code]

Hoang, N., Nie, D.,  Taivanbat B.., Cheng L.. Eddie-Transformer: Enriched Disease Embedding Transformer for X-Ray Report Generation.  ISBI 2022. [pdf][code] (Oral)

Szalkowski, G., Nie, D., Zhu, T., Yap, P. T., & Lian, J. . Synthetic Digital Reconstructed Radiographs for MR-only Robotic Stereotactic Radiation Therapy: A Proof of Concept. Computers in Biology and Medicine, 2021. [pdf]

Hoang, N.#, Nie, D.#,  Taivanbat B.., Cheng L.. Automated Generation of Accurate & Fluent Medical X-ray Reports.  EMNLP 2021. [pdf][code]  (My first supervised project with my student, Proud of Hoang!)

Nie, D., Xue, J., Ren, X. Bidirectional Pyramid Networks for Semantic Segmentation. ACCV 2020. [pdf][code] (Oral)

Nie, D., Shen, D. Adversarial Confidence Learning for Medical Image Analysis. International Journal of Computer Vision. 2020. [pdf][code]

Zhou, S., Nie, D., Shen, D.. High-Resolution Encoder-Decoder Networks for Low-Contrast Medical Image Segmentation, IEEE Transactions on Image Processing, 2019. [pdf]

Wang, L.#, Nie, D.#,..., Shen, D.. Benchmark on Automatic 6-month-old Infant Brain Segmentation Algorithms: The iSeg-2017 Challenge, IEEE Transactions on Medical Imaging, 2019. [pdf]

Nie, D., ... and Shen D.. Multi-Channel 3D Deep Feature Learning for Survival Time Prediction of Brain Tumor Patients Using Multi-Modal Neuroimages. Nature Scientific Reports, 2018. [pdf]

Nie, D., Wang, L., Xiang, L., Zhou, S., Adeli, E., Shen, D.. Difficulty-Aware Attention Network with Confidence Learning for Medical Image Segmentation. AAAI, Honolulu, Hawaii, Jan. 27-Feb. 1, 2019. [pdf][code] (Spotlight)

Nie, D., Wang, L., Gao, Y., Lian, J., Shen, D.. STRAINet: Spatially-varying sTochastic Residual AdversarIal Networks for MRI Pelvic Organ Segmentation. IEEE Transactions on Neural Networks and Learning Systems, 2018. [pdf][code]

Nie, D., Gao, Y., Wang, L., Shen, D.. ASDNet: Attention based Semi-supervised Deep Networks for BioMedical Image Segmentation. MICCAI, Granada, Spain, 2018. [pdf][code]

Nie, D., Trullo, R., Lian, J., Wang, L., Petitjean, C., Ruan, S., Wang, Q., Shen, D.. Medical Image Synthesis with Deep Convolutional Adversarial Networks. IEEE Transactions on Biomedical Engineering, 2018. [pdf][code] (ESI high citation)

Nie, D., Wang, L., Adeli, E., Lao, C., Lin, W., Shen, D.. 3D Fully Convolutional Networks for Multi-Modal Isointense Infant Brain Image Segmentation, IEEE Transactions on Cybernetics, 2018. [pdf][code]

Nie, D*, Trullo, R., Petitjean, C., Ruan, S., and Shen, D.. Medical Image Synthesis with Context-aware Generative Adversarial Networks. MICCAI, Quebec, Canada, 2017. Uploaded to arxiv. [pdf][code] (This was firstly uploaded to arxiv in Dec. 2016 and it was an independent work from pixel-to-pixel which was on-going simultaneously) (MICCAI Young Scientist Publication Impact Award)

Nie, D., Zhang, H., Adeli, E., Liu, L., Shen, D.. 3D Deep Learning for Multi-modal Imaging-guided Survival Time Prediction of Brain Tumor Patients, MICCAI, Athens, Greece, 2016.[pdf] [code]

Nie, D., Wang, L., Gao, Y., Shen, D.. Fully convolutional networks for multi-modality isointense infant brain image segmentation. ISBI 2016: 1342-1345 [pdf] [code] (Best Student Paper Finalist)

Nie, D., Shank, E., Jojic, V.. A deep framework for bacterial image segmentation and classification. ACM BCB 2015: 306-314 [pdf] [code] (Oral)

Nie, D., Yan, Z., Zhao, N., Zhu, T.. A Pilot Study of Comparing Social Network Behaviors between Onlies and Others. IJCBPL 5(3): 56-66 (2015) [pdf]

Nie, D., Guan, Z., Hao, B., Bai, S., Zhu, T.. Predicting Personality on Social Media with Semi-supervised Learning. WI  2014: 158-165 [pdf] [code] [Oral]

Guan, Z., Nie, D., Hao, B., Bai, S., Zhu, T.. Local Regression Transfer Learning for Users' Personality Prediction. AMT 2014: 23-34 [pdf]

Nie, D., Hong, L., Zhu, T.. Movie Recommendation Using Unrated Data. ICMLA (1) 2013: 344-347 [pdf]

Selected Abstracts and Workshops:

Nie, D., Wang, L., Lian, J., Shen, D.. Pelvic Organ Segmentation with Sample Attention based Stochastic Connection Networks. ISMRM, Paris, France. June, 2018. [pdf][code]

Nie, D., Wang, L., ... ,Shen, D.. Segmentation of Craniomaxillofacial Bony Structures from MRI with A Cascade Deep Learning Framework, MLMI, Quebec, Canada, 2017. [pdf][code] (Oral)

Nie, D., Li Wang, Jianfu Li, Daeseung Kim, James Xia, Dinggang Shen. Segmentation of CMF Bones from MRI with A Cascade Deep Learning Framework, ISMRM, Hawaii, USA, April 22 - 27, 2017. [coming soon]

Nie, D., Li Wang, Roger Trullo, Ehsan Adeli, Weili Lin, Dinggang Shen. Multi-modal Isointense Infant Brain Image Segmentation with Deep Learning based Methods, ISMRM, Hawaii, USA, April 22 - 27, 2017.  (Oral) [coming soon][code]

Nie, D., Cao, X., Gao, Y., Wang, L., Shen, D.. Estimating CT images from MRI using 3D Fully Convolutional Networks. DLMIA, Athens, Greece, 2016. [coming soon][code] (Oral)

Nie, D., Ning, Y., Zhu, T.. Predicting Mental Health Status in the Context of Web Browsing. WI-IAT Workshops 2012 [pdf][code] (Oral)