no code implementations • 27 Dec 2023 • Jingqi Niu, Qinji Yu, Shiwen Dong, Zilong Wang, Kang Dang, Xiaowei Ding
Detecting anomalies in fundus images through unsupervised methods is a challenging task due to the similarity between normal and abnormal tissues, as well as their indistinct boundaries.
no code implementations • 7 Mar 2023 • Jingqi Niu, Shiwen Dong, Qinji Yu, Kang Dang, Xiaowei Ding
ReSAD transfers a pre-trained model to extract the features of normal fundus images and applies the Region-and-Spatial-Aware feature Combination module (ReSC) for pixel-level features to build a memory bank.
1 code implementation • 14 Oct 2022 • Jin Ye, Haoyu Wang, Ziyan Huang, Zhongying Deng, Yanzhou Su, Can Tu, Qian Wu, Yuncheng Yang, Meng Wei, Jingqi Niu, Junjun He
The combination of PET-based metabolic and CT-based anatomic information can contribute to better tumor segmentation results.
no code implementations • 6 Sep 2022 • Haoyu Wang, Ziyan Huang, Jin Ye, Can Tu, Yuncheng Yang, Shiyi Du, Zhongying Deng, Chenglong Ma, Jingqi Niu, Junjun He
Renal structure segmentation from computed tomography angiography~(CTA) is essential for many computer-assisted renal cancer treatment applications.