2 code implementations • 12 Aug 2021 • Mohammad Reza Hosseinzadeh Taher, Fatemeh Haghighi, Ruibin Feng, Michael B. Gotway, Jianming Liang
Transfer learning from supervised ImageNet models has been frequently used in medical image analysis.
2 code implementations • 19 Aug 2019 • Zongwei Zhou, Vatsal Sodha, Md Mahfuzur Rahman Siddiquee, Ruibin Feng, Nima Tajbakhsh, Michael B. Gotway, Jianming Liang
More importantly, learning a model from scratch simply in 3D may not necessarily yield performance better than transfer learning from ImageNet in 2D, but our Models Genesis consistently top any 2D approaches including fine-tuning the models pre-trained from ImageNet as well as fine-tuning the 2D versions of our Models Genesis, confirming the importance of 3D anatomical information and significance of our Models Genesis for 3D medical imaging.
Ranked #1 on Pulmonary Embolism Detection on PE-CAD FPRED
1 code implementation • ICCV 2019 • Md Mahfuzur Rahman Siddiquee, Zongwei Zhou, Nima Tajbakhsh, Ruibin Feng, Michael B. Gotway, Yoshua Bengio, Jianming Liang
Qualitative and quantitative evaluations demonstrate that the proposed method outperforms the state of the art in multi-domain image-to-image translation and that it surpasses predominant weakly-supervised localization methods in both disease detection and localization.
no code implementations • 30 May 2018 • Hao Wang, Ruibin Feng, Chi-Sing Leung
Simulation results show that the proposed sparse approximation method has the real-time solutions with satisfactory MSEs.
no code implementations • 30 May 2018 • Hao Wang, Chi-Sing Leung, Hing Cheung So, Ruibin Feng, Zifa Han
The aim of this paper is to train an RBF neural network and select centers under concurrent faults.