no code implementations • 22 Jul 2018 • Mitko Veta, Yujing J. Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A. Shah, Dayong Wang, Mikael Rousson, Martin Hedlund, David Tellez, Francesco Ciompi, Erwan Zerhouni, David Lanyi, Matheus Viana, Vassili Kovalev, Vitali Liauchuk, Hady Ahmady Phoulady, Talha Qaiser, Simon Graham, Nasir Rajpoot, Erik Sjöblom, Jesper Molin, Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Zhipeng Jia, Eric I-Chao Chang, Yan Xu, Andrew H. Beck, Paul J. van Diest, Josien P. W. Pluim
The best performing automatic method for the first task achieved a quadratic-weighted Cohen's kappa score of $\kappa$ = 0. 567, 95% CI [0. 464, 0. 671] between the predicted scores and the ground truth.
2 code implementations • 2 Aug 2017 • Sangheum Hwang, Sunggyun Park
We introduce an accurate lung segmentation model for chest radiographs based on deep convolutional neural networks.
1 code implementation • 21 Dec 2016 • Kyunghyun Paeng, Sangheum Hwang, Sunggyun Park, Minsoo Kim
We present a unified framework to predict tumor proliferation scores from breast histopathology whole slide images.
no code implementations • 20 Dec 2016 • Donggeun Yoo, Sunggyun Park, Kyunghyun Paeng, Joon-Young Lee, In So Kweon
In this paper, we present an "action-driven" detection mechanism using our "top-down" visual attention model.
1 code implementation • 24 Mar 2016 • Donggeun Yoo, Namil Kim, Sunggyun Park, Anthony S. Paek, In So Kweon
We present an image-conditional image generation model.
no code implementations • ICCV 2015 • Donggeun Yoo, Sunggyun Park, Joon-Young Lee, Anthony S. Paek, In So Kweon
We present a novel detection method using a deep convolutional neural network (CNN), named AttentionNet.
no code implementations • 4 Dec 2014 • Donggeun Yoo, Sunggyun Park, Joon-Young Lee, In So Kweon
In this paper, we present a straightforward framework for better image representation by combining the two approaches.