no code implementations • 27 May 2022 • Jingtang Liang, Chi-Man Pun
Our method attempts to bring together corresponding positive and negative samples by maximizing the mutual information between the foreground and background styles, which desirably makes our harmonization network more robust to discriminate the foreground and background style features when harmonizing composite images.
no code implementations • 6 Apr 2022 • Marc Aubreville, Nikolas Stathonikos, Christof A. Bertram, Robert Klopleisch, Natalie ter Hoeve, Francesco Ciompi, Frauke Wilm, Christian Marzahl, Taryn A. Donovan, Andreas Maier, Jack Breen, Nishant Ravikumar, Youjin Chung, Jinah Park, Ramin Nateghi, Fattaneh Pourakpour, Rutger H. J. Fick, Saima Ben Hadj, Mostafa Jahanifar, Nasir Rajpoot, Jakob Dexl, Thomas Wittenberg, Satoshi Kondo, Maxime W. Lafarge, Viktor H. Koelzer, Jingtang Liang, YuBo Wang, Xi Long, Jingxin Liu, Salar Razavi, April Khademi, Sen yang, Xiyue Wang, Mitko Veta, Katharina Breininger
The goal of the MICCAI MIDOG 2021 challenge has been to propose and evaluate methods that counter this domain shift and derive scanner-agnostic mitosis detection algorithms.
2 code implementations • 13 Sep 2021 • Jingtang Liang, Xiaodong Cun, Chi-Man Pun, Jue Wang
To this end, we propose a novel spatial-separated curve rendering network(S$^2$CRNet) for efficient and high-resolution image harmonization for the first time.
Ranked #12 on Image Harmonization on iHarmony4
no code implementations • 31 Aug 2021 • Jingtang Liang, Cheng Wang, Yujie Cheng, Zheng Wang, Fang Wang, Liyu Huang, Zhibin Yu, YuBo Wang
Mitotic figure count is an important marker of tumor proliferation and has been shown to be associated with patients' prognosis.