Research output per year
Research output per year
- 14 results
Search results
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2024
Multi-Scale Tokens-Aware Transformer Network for Multi-Region and Multi-Sequence MR-to-CT Synthesis in a Single Model
Zhong, L., Chen, Z., Shu, H., Zheng, K., Li, Y., Chen, W., Wu, Y., Ma, J., Feng, Q. & Yang, W., Feb 1 2024, In: IEEE Transactions on Medical Imaging. 43, 2, p. 794-806 13 p.Research output: Contribution to journal › Article › peer-review
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2023
A generic fundus image enhancement network boosted by frequency self-supervised representation learning
Li, H., Liu, H., Fu, H., Xu, Y., Shu, H., Niu, K., Hu, Y. & Liu, J., Dec 2023, In: Medical Image Analysis. 90, 102945.Research output: Contribution to journal › Article › peer-review
Open Access -
Cross-Task Feedback Fusion GAN for Joint MR-CT Synthesis and Segmentation of Target and Organs-at-Risk
Zhang, Y., Zhong, L., Shu, H., Dai, Z., Zheng, K., Chen, Z., Feng, Q., Wang, X. & Yang, W., Oct 1 2023, In: IEEE Transactions on Artificial Intelligence. 4, 5, p. 1246-1257 12 p.Research output: Contribution to journal › Article › peer-review
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QACL: Quartet attention aware closed-loop learning for abdominal MR-to-CT synthesis via simultaneous registration
Zhong, L., Chen, Z., Shu, H., Zheng, Y., Zhang, Y., Wu, Y., Feng, Q., Li, Y. & Yang, W., Jan 2023, In: Medical Image Analysis. 83, 102692.Research output: Contribution to journal › Article › peer-review
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United multi-task learning for abdominal contrast-enhanced CT synthesis through joint deformable registration
Zhong, L., Huang, P., Shu, H., Li, Y., Zhang, Y., Feng, Q., Wu, Y. & Yang, W., Apr 2023, In: Computer Methods and Programs in Biomedicine. 231, 107391.Research output: Contribution to journal › Article › peer-review
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2022
A Comparative Study of non-deep Learning, Deep Learning, and Ensemble Learning Methods for Sunspot Number Prediction
Dang, Y., Chen, Z., Li, H. & Shu, H., 2022, In: Applied Artificial Intelligence. 36, 1, 2074129.Research output: Contribution to journal › Article › peer-review
Open Access -
CDPA: Common and distinctive pattern analysis between high-dimensional datasets
Shu, H. & Qu, Z., 2022, In: Electronic Journal of Statistics. 16, 1, p. 2475-2517 43 p.Research output: Contribution to journal › Article › peer-review
Open Access -
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data.
Shu, H., Qu, Z. & Zhu, H., Jun 1 2022, In: Journal of Machine Learning Research. 23Research output: Contribution to journal › Article › peer-review
Open Access -
2021
A deep learning approach to re-create raw full-field digital mammograms for breast density and texture analysis
Shu, H., Chiang, T., Wei, P., Do, K. A., Lesslie, M. D., Cohen, E. O., Srinivasan, A., Moseley, T. W., Chang Sen, L. Q., Leung, J. W. T., Dennison, J. B., Hanash, S. M. & Weaver, O. O., 2021, In: Radiology: Artificial Intelligence. 3, 4, e200097.Research output: Contribution to journal › Article › peer-review
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2020
(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients
Zhong, L., Li, T., Shu, H., Huang, C., Michael Johnson, J., Schomer, D. F., Liu, H. L., Feng, Q., Yang, W. & Zhu, H., Dec 2020, In: NeuroImage. 223, 117368.Research output: Contribution to journal › Article › peer-review
Open Access -
D-CCA: A Decomposition-Based Canonical Correlation Analysis for High-Dimensional Datasets
Shu, H., Wang, X. & Zhu, H., Jan 2 2020, In: Journal of the American Statistical Association. 115, 529, p. 292-306 15 p.Research output: Contribution to journal › Article › peer-review
Open Access -
2019
Assessment of network module identification across complex diseases
The DREAM Module Identification Challenge Consortium, Sep 1 2019, In: Nature methods. 16, 9, p. 843-852 10 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Estimation of large covariance and precision matrices from temporally dependent observations
Shu, H. & Nan, B., Jan 2019, In: Annals of Statistics. 47, 3, p. 1321-1350 30 p.Research output: Contribution to journal › Article › peer-review
Open Access -
2015
Multiple testing for neuroimaging via hidden Markov random field
Shu, H., Nan, B. & Koeppe, R., Sep 1 2015, In: Biometrics. 71, 3, p. 741-750 10 p.Research output: Contribution to journal › Article › peer-review
Open Access