Publication

See google scholar for the full publication list.

Citations in latex bib format. The source code in AITom publication list.

Selected publications

  1. [CV] Metric from Human: Zero-shot Monocular Metric Depth Estimation via Test-time Adaptation. NeurIPS 2024. paper
  2. [ET] CryoSAM: Training-free CryoET Tomogram Segmentation with Foundation Models. Medical Image Computing & Computer Assisted Intervention (MICCAI) 2024. doi:10.48550/arXiv.2407.06833
  3. [AS, CV] Deep Video Anomaly Detection in Automated Laboratory Setting. SSRN Preprint. doi:10.2139/ssrn.4887151
  4. [AS,CV] Cross-Domain Learning for Video Anomaly Detection with Limited Supervision. European Conference on Computer Vision (ECCV) 2024. doi:10.1007/978-3-031-73404-5_27 doi:10.48550/arXiv.2408.05191
  5. [ET] DUAL: deep unsupervised simultaneous simulation and denoising for cryo-electron tomography. bioRxiv. doi:10.1101/2024.03.02.583135
  6. [CV] One-Prompt to Segment All Medical Images. IEEE conference on computer vision and pattern recognition (CVPR) 2024. doi:10.48550/arXiv.2305.10300
  7. [ET] High-throughput cryo-ET structural pattern mining by deep unsupervised clustering. Proceedings of the National Academy of Sciences. doi:10.1073/pnas.2213149120
  8. [AS,CV] Detecting Anomalies from Liquid Transfer Videos in Automated Laboratory Setting. Frontiers in Molecular Biosciences. doi:10.3389/fmolb.2023.1147514
  9. [CV,ML,ET,EM] Harmony: A Generic Unsupervised Approach for Disentangling Semantic Content from Parameterized Transformations. IEEE conference on computer vision and pattern recognition (CVPR 2022). Paper
  10. [ML] Boosting Active Learning via Improving Test Performance. AAAI Conference on Artificial Intelligence (AAAI) 2022. arXiv:2112.05683
  11. [CV,ET] End-to-end robust joint unsupervised image alignment and clustering. International Conference on Computer Vision (ICCV 2021). doi:10.1109/iccv48922.2021.00383
  12. [CV,ET] Weakly Supervised 3D Semantic Segmentation Using Cross-Image Consensus and Inter-Voxel Affinity Relations. International Conference on Computer Vision (ICCV 2021). doi:10.1109/icv48922.2021.00283
  13. [ET] Active learning to classify macromolecular structures in situ for less supervision in cryo-electron tomography. Bioinformatics. doi:10.1093/bioinformatics/btab123 arXiv:2102.12040
  14. [ET] Gum-Net: Unsupervised geometric matching for fast and accurate 3D subtomogram image alignment and averaging. In Proceedings of the IEEE conference on computer vision and pattern recognition (CVPR 2020). Paper
  15. [ET] Few-shot learning for classification of novel macromolecular structures in cryo-electron tomograms. PLOS Computational Biology. doi:10.1371/journal.pcbi.1008227
  16. [ET] Open-set Recognition of Unseen Macromolecules in Cellular Electron Cryo-Tomograms by Soft Large Margin Centralized Cosine Loss. British Machine Vision Conference (BMVC 2019 spotlight with acceptance rate < 5%). pdf
  17. [ET] Respond-CAM: Analyzing Deep Models for 3D Imaging Data by Visualizations. Medical Image Computing & Computer Assisted Intervention (MICCAI) 2018. arXiv:1806.00102
  18. [ET] An integration of fast alignment and maximum-likelihood methods for electron subtomogram averaging and classification. ISMB 2018. Bioinformatics. 2018 Jul 1; 34(13): i227–i236. doi:10.1093/bioinformatics/bty267.
  19. [ET] A convolutional autoencoder approach for mining features in cellular electron cryo-tomograms and weakly supervised coarse segmentation. Journal of Structural Biology. 2018 May;202(2):150-160. doi:10.1016/j.jsb.2017.12.015 [code]
  20. [ET] De novo structural pattern mining in cellular electron cryo-tomograms. Structure. 2019 Apr 2;27(4):679-691.e14. doi:10.1016/j.str.2019.01.005. (Appeared on Structure volume cover and highlighted in Nature Methods 16, page 285 (2019), doi:10.1038/s41592-019-0382-2)
  21. [OM] Learn to segment single cells with deep distance estimator and deep cell detector. Computers in Biology and Medicine. doi:10.1016/j.compbiomed.2019.04.006
  22. [ET] High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching. Journal of Structural Biology. 2012 May;178(2):152-64. Epub 2012 Mar 7. doi:10.1016/j.jsb.2012.02.014
  23. [GE] Automated multidimensional phenotype profiling using large public microarray repositories. Proc Natl Acad Sci U S A. (PNAS). 2009; 106(30), 12323 - 12328. (Highlighted in Nature Methods 6, 632; Selected and re-published in 2010 International Medical Informatics Association Yearbook of Medical Informatics) doi:10.1073/pnas.0900883106
  24. [GE] An integrative approach to characterize disease-specific pathways and their coordination: a case study in cancer. BMC Genomics. 2008; 9 Suppl 1:S12. doi:10.1186/1471-2164-9-S1-S12

Categories:

  • ET: Cryo-Electron Tomography
  • EM: Cryo-Electron Microscopy
  • AS: Automated Science
  • CV: Computer Vision
  • ML: Machine Learning
  • OM: Optical Microscopy
  • GE: Computational Genomics