1 code implementation • 17 Nov 2023 • Can Li, Sheng Shao, Junyi Qu, Shuchao Pang, Mehmet A. Orgun
However, due to the fact that medical image annotation requires a great deal of manpower and expertise, as well as the fact that clinical departments perform image annotation based on task orientation, there is the problem of having fewer medical image annotation data with more unlabeled data and having many datasets that annotate only a single organ.
no code implementations • 29 Jul 2022 • Shuchao Pang, Anan Du, Mehmet A. Orgun, Yan Wang, Quan Z. Sheng, Shoujin Wang, Xiaoshui Huang, Zhenmei Yu
Automatic tumor or lesion segmentation is a crucial step in medical image analysis for computer-aided diagnosis.
1 code implementation • 13 May 2021 • Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu
Recent years have witnessed the fast development of the emerging topic of Graph Learning based Recommender Systems (GLRS).
no code implementations • 8 May 2020 • Shuchao Pang, Anan Du, Mehmet A. Orgun, Yan Wang, Quanzheng Sheng, Shoujin Wang, Xiaoshui Huang, Zhemei Yu
To mitigate this shortcoming, we propose a novel group equivariant segmentation framework by encoding those inherent symmetries for learning more precise representations.