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Hongmin Bai
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2020 – today
- 2020
- [j2]Ahmed Elazab
, Changmiao Wang
, Syed Jamal Safdar Gardezi
, Hongmin Bai, Qingmao Hu, Tianfu Wang, Chunqi Chang
, Baiying Lei
:
GP-GAN: Brain tumor growth prediction using stacked 3D generative adversarial networks from longitudinal MR Images. Neural Networks 132: 321-332 (2020) - [c4]Ahmed Elazab
, Changmiao Wang
, Syed Jamal Safdar Gardezi
, Hongmin Bai, Tianfu Wang, Baiying Lei, Chunqi Chang
:
Glioma Growth Prediction via Generative Adversarial Learning from Multi-Time Points Magnetic Resonance Images. EMBC 2020: 1750-1753
2010 – 2019
- 2019
- [j1]Ahmed El-Azab
, Ahmed M. Anter
, Hongmin Bai, Qingmao Hu, Zakir Hussain, Dong Ni, Tianfu Wang, Baiying Lei:
An optimized generic cerebral tumor growth modeling framework by coupling biomechanical and diffusive models with treatment effects. Appl. Soft Comput. 80: 617-627 (2019) - [c3]Zijia Liu, Qiuchang Sun, Hongmin Bai, Chaofeng Liang, Yinsheng Chen, Zhi-Cheng Li
:
3D Deep Attention Network for Survival Prediction from Magnetic Resonance Images in Glioblastoma. ICIP 2019: 1381-1384 - 2018
- [c2]Ahmed El-Azab
, Hongmin Bai, Mengya Yang, Qingmao Hu, Minh Hung Le, Tianfu Wang
, Baiying Lei:
A Coupled Modified Reaction Diffusion and Biomechanical Models for Cerebral Tumor Growth Modeling in Presence of Treatment. EMBC 2018: 758-761 - 2017
- [c1]Ahmed El-Azab
, Hongmin Bai, Xiaodong Zhang, Qingmao Hu:
Low grade glioma growth modeling considering chemotherapy and radiotherapy effects from magnetic resonance images. EMBC 2017: 3077-3080
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