Chia-Ling (Charlene) Tsai

Current PhD Students

Jiaqi Yang

PhD Candidate

[Google Scholar] [Website] [Github]

J. Yang, N. Mehta, G. M. Demirci, X. Hu, M. S. Ramakrishnan, M. Naguib, C. Chen and C.-L. Tsai. “Anomaly-Guided Weakly Supervised Lesion Segmentation on Retinal OCT Images”, Medical Image Analysis, 2024
J. Yang, X. Hu, C. Chen, and C.-L. Tsai. “A Topological-Attention ConvLSTM Network and Its Application to EM Images”, Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021, September.
J. Yang, X. Hu, C. Chen, and C.-L. Tsai. “3D Topology-Preserving Segmentation with Compound Multi-Slice Representation”, International Symposium on Biomedical Imaging (ISBI), 2021, April.

Gozde Demirci

PhD Candidate

[Google Scholar] [Website] [Github]

G. M. Demirci, P. Kittler, M.J. Flory, H.T. Phan, A. Gordon, S. Parab, and C.-L. Tsai. "Predicting mental and psychomotor delay in very pre-term infants using machine learning", Pediatr Res, 2023. https://doi.org/10.1038/s41390-023-02713-z
G. M. Demirci, D. Delngeniis, W. M. Wong, D. Sheeren, Y. Nomura and C.-L. Tsai, "Superstorm Sandy exposure in utero is associated with neurobehavioral phenotypes and brain structure alterations in childhood: A machine learning approach", Frontiers in Neuroscience, 2023. https://doi.org/10.3389/fnins.2023.1113927
G. M. Demirci, C.-L. Tsai, M.J. Flory, H.T. Phan, A. Gordon, S. Parab, and P. Kittler, “Predicting Developmental Delay in Very Pre-Term Infants Using Machine Learning”, Association for Psychological Science (APS) Annual Convention, 2022, May.

Former MS Students (co-supervising with Wei-Yang Lin)

Kai-Hsuan Lin (2023)

T.-H. Yang, Y.-Y. Su, C.-L Tsai, K.-H. Lin, W.-Y. Lin and S.-F. Sung. “Magnetic resonance imaging-based deep learning imaging biomarker for predicting functional outcomes after acute ischemic stroke”, European Journal of Radiology, 2024

Hui-Yun Su (2023)

C.-L Tsai, H.-Y. Su, W.-Y. Lin Y.-Y. Su, T.-H. Yang M.-L. Mai and S.-F. Sung, “Fusion of Diffusion Weighted MRI and Clinical Data for Predicting Functional Outcome after Acute Ischemic Stroke with Deep Contrastive Learning”, https://arxiv.org/abs/2402.10894

Ming-Chi Liu (2022)

M.-C. Liu, and W.-Y. Lin and C.-L Tsai. “Computer-Aided Response-to-Intervention for Reading Comprehension Based on Recommender System”, International Conference on Artificial Intelligence in Education, 2022, July.

Cheng-Ho King (2021)

C.-H. King, Y.-L. Wang, W.-Y. Lin, and C.-L. Tsai. “Automatic Cephalometric Landmark Detection on X-Ray Images using Object Detection”, International Symposium on Biomedical Imaging, 2022, March.

Yu-Yeh Tsai (2021)

Y.-Y. Tsai, W.-Y. Lin, S.-J. Chen, P. Ruamviboonsuk, C.-Ho. King, and C.-L. Tsai. “Early diagnosis of Polypoidal Choroidal Vasculopathy from Fluorescein Angiography Using Deep Learning”, Translational Vision Science & Technology, 2022, February, https://tvst.arvojournals.org/article.aspx?articleid=2778345

Yong-Guei Lin (2019)

C.-L. Tsai, Y.-G. Lin, and M.-C. Liu, and W.-Y. Lin. “Computer-Aided Grouping of Students with Reading Disabilities for Effective Response-to-Intervention”, 16th International Conference on Intelligent Tutoring Systems, 2020, June.

C.-L. Tsai, Y.-G. Lin, W.-Y. Lin, and M. Zakierski. “Computer-Aided Intervention for Reading Comprehension Disabilities”, 15th International Conference on Intelligent Tutoring Systems, 2019, June.