no code implementations • 4 Dec 2020 • Ngan Le, Trung Le, Kashu Yamazaki, Toan Duc Bui, Khoa Luu, Marios Savides
Our proposed Offset Curves (OsC) loss consists of three main fitting terms.
no code implementations • 3 Dec 2020 • Toan Duc Bui, Manh Nguyen, Ngan Le, Khoa Luu
To capture temporal structures in the medical images, we explore the displacement between the consecutive slices using a deformation field.
Generative Adversarial Network Image-to-Image Translation +1
no code implementations • 4 Jul 2020 • Yue Sun, Kun Gao, Zhengwang Wu, Zhihao Lei, Ying WEI, Jun Ma, Xiaoping Yang, Xue Feng, Li Zhao, Trung Le Phan, Jitae Shin, Tao Zhong, Yu Zhang, Lequan Yu, Caizi Li, Ramesh Basnet, M. Omair Ahmad, M. N. S. Swamy, Wenao Ma, Qi Dou, Toan Duc Bui, Camilo Bermudez Noguera, Bennett Landman, Ian H. Gotlib, Kathryn L. Humphreys, Sarah Shultz, Longchuan Li, Sijie Niu, Weili Lin, Valerie Jewells, Gang Li, Dinggang Shen, Li Wang
Deep learning-based methods have achieved state-of-the-art performance; however, one of major limitations is that the learning-based methods may suffer from the multi-site issue, that is, the models trained on a dataset from one site may not be applicable to the datasets acquired from other sites with different imaging protocols/scanners.
no code implementations • Biomedical Signal Processing and Control 2019 • Toan Duc Bui, Jitae Shin, Taesup Moon
The proposed network, called 3D-SkipDenseSeg, exploits the advantage of the recently DenseNet for classification task and extends this to segment the 6-month infant brain tissue segmentation of magnetic resonance imaging (MRI).
1 code implementation • arXiv preprint 2017 • Toan Duc Bui, Jitae Shin, Taesup Moon
The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.
1 code implementation • 11 Sep 2017 • Toan Duc Bui, Jitae Shin, Taesup Moon
The proposed network architecture provides a dense connection between layers that aims to improve the information flow in the network.