Ba Thinh Lam

According to our database, Ba Thinh Lam authored at least 8 papers between 2023 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

UP2D: Uncertainty-aware progressive pseudo-label denoising for source-free domain adaptive medical image segmentation.

Thanh-Huy Nguyen, Quang-Khai Bui-Tran, Manh D. Ho, Ba Thinh Lam, Vi Vu, Hoang-Thien Nguyen, Phat K. Huynh, Ulas Bagci

Neurocomputing, 2026

2025

Adaptive Knowledge Transferring with Switching Dual-Student Framework for Semi-Supervised Medical Image Segmentation.

Thanh-Huy Nguyen, Hoang-Thien Nguyen, Ba Thinh Lam, Vi Vu, Bach X. Nguyen, Jianhua Xing, Tianyang Wang, Xingjian Li, Min Xu

CoRR, October, 2025

Label-Efficient Cross-Modality Generalization for Liver Segmentation in Multi-Phase MRI.

Quang-Khai Bui-Tran, Minh-Toan Dinh, Thanh-Huy Nguyen, Ba Thinh Lam, Mai-Anh Vu, Ulas Bagci

CoRR, October, 2025

Describe Anything in Medical Images.

Xi Xiao, Yunbei Zhang, Thanh-Huy Nguyen, Ba Thinh Lam, Janet Wang, Lin Zhao, Jihun Hamm, Tianyang Wang, Xingjian Li, Xiao Wang, Hao Xu, Tianming Liu, Min Xu

CoRR, May, 2025

DuetMatch: Harmonizing semi-supervised brain MRI segmentation via decoupled branch optimization.

Thanh-Huy Nguyen, Hoang-Thien Nguyen, Vi Vu, Ba Thinh Lam, Phat Huynh, Tianyang Wang, Xingjian Li, Ulas Bagci, Min Xu

Comput. Medical Imaging Graph., 2025

2024

Dual Dynamic Consistency Regularization for Semi-Supervised Domain Adaptation.

Ba Hung Ngo, Ba Thinh Lam, Thanh-Huy Nguyen, Quang Vinh Dinh, Tae Jong Choi

IEEE Access, 2024

2023

Delving into Ipsilateral Mammogram Assessment under Multi-View Network.

Thai Ngoc Toan Truong, Thanh-Huy Nguyen, Ba Thinh Lam, Vu Minh Duy Nguyen, Hong Phuc Nguyen

CoRR, 2023

Towards Robust Natural-Looking Mammography Lesion Synthesis on Ipsilateral Dual-Views Breast Cancer Analysis.

Thanh-Huy Nguyen, Quang-Hien Kha, Thai Ngoc Toan Truong, Ba Thinh Lam, Ba Hung Ngo, Quang Vinh Dinh, Nguyen-Quoc-Khanh Le

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023