no code implementations • ECCV 2020 • Yanda Meng, Wei Meng, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Xiaowei Huang, Yalin Zheng
In particular, thanks to the proposed aggregation GCN, our network benefits from direct feature learning of the instances’ boundary locations and the spatial information propagation across the image.
no code implementations • 25 Nov 2023 • Jack Wells, Amirafshar Moshtaghpour, Daniel Nicholls, Alex W. Robinson, Yalin Zheng, Jony Castagna, Nigel D. Browning
Despite their proven success and broad applicability to Electron Microscopy (EM) data, joint dictionary-learning and sparse-coding based inpainting algorithms have so far remained impractical for real-time usage with an Electron Microscope.
no code implementations • 10 Nov 2023 • Shouyue Liu, Jinkui Hao, Yanwu Xu, Huazhu Fu, Xinyu Guo, Jiang Liu, Yalin Zheng, Yonghuai Liu, Jiong Zhang, Yitian Zhao
Optical Coherence Tomography Angiography (OCTA) is a promising tool for detecting Alzheimer's disease (AD) by imaging the retinal microvasculature.
no code implementations • 27 Apr 2023 • Yuchen Zhang, Yanda Meng, Yalin Zheng
Accurate segmentation of the left atrial (LA) and LA scars can provide valuable information to predict treatment outcomes in AF.
1 code implementation • CVPR 2023 • Hongrun Zhang, Liam Burrows, Yanda Meng, Declan Sculthorpe, Abhik Mukherjee, Sarah E Coupland, Ke Chen, Yalin Zheng
Image segmentation is a fundamental task in the field of imaging and vision.
1 code implementation • CVPR 2022 • Hongrun Zhang, Yanda Meng, Yitian Zhao, Yihong Qiao, Xiaoyun Yang, Sarah E. Coupland, Yalin Zheng
Multiple instance learning (MIL) has been increasingly used in the classification of histopathology whole slide images (WSIs).
no code implementations • 9 Mar 2022 • Yanda Meng, Xu Chen, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Yihong Qiao, Xiaowei Huang, Yalin Zheng
In this paper, we propose a novel multi-level aggregation network to regress the coordinates of the vertices of a 3D face from a single 2D image in an end-to-end manner.
1 code implementation • 8 Mar 2022 • Yanda Meng, Joshua Bridge, Meng Wei, Yitian Zhao, Yihong Qiao, Xiaoyun Yang, Xiaowei Huang, Yalin Zheng
This paper proposes an adaptive auxiliary task learning based approach for object counting problems.
1 code implementation • 27 Oct 2021 • Yanda Meng, Hongrun Zhang, Dongxu Gao, Yitian Zhao, Xiaoyun Yang, Xuesheng Qian, Xiaowei Huang, Yalin Zheng
Our model is well-suited to obtain global semantic region information while also accommodates local spatial boundary characteristics simultaneously.
1 code implementation • ICCV 2021 • Yanda Meng, Hongrun Zhang, Yitian Zhao, Xiaoyun Yang, Xuesheng Qian, Xiaowei Huang, Yalin Zheng
Semi-supervised approaches for crowd counting attract attention, as the fully supervised paradigm is expensive and laborious due to its request for a large number of images of dense crowd scenarios and their annotations.
no code implementations • 26 Feb 2021 • Shuai Yu, Jianyang Xie, Jinkui Hao, Yalin Zheng, Jiong Zhang, Yan Hu, Jiang Liu, Yitian Zhao
Experimental results demonstrate that our method is effective in the depth prediction and 3D vessel reconstruction for OCTA images.% results may be used to guide subsequent vascular analysis
1 code implementation • 1 Nov 2020 • Xu Chen, Xiangde Luo, Yitian Zhao, Shaoting Zhang, Guotai Wang, Yalin Zheng
Inspired by Euler's Elastica model and recent active contour models introduced into the field of deep learning, we propose a novel active contour with elastica (ACE) loss function incorporating Elastica (curvature and length) and region information as geometrically-natural constraints for the image segmentation tasks.
1 code implementation • 15 Oct 2020 • Lei Mou, Yitian Zhao, Huazhu Fu, Yonghuai Liu, Jun Cheng, Yalin Zheng, Pan Su, Jianlong Yang, Li Chen, Alejandro F Frang, Masahiro Akiba, Jiang Liu
Automated detection of curvilinear structures, e. g., blood vessels or nerve fibres, from medical and biomedical images is a crucial early step in automatic image interpretation associated to the management of many diseases.
no code implementations • 10 Jul 2020 • Joshua Bridge, Simon P. Harding, Yalin Zheng
We propose a novel deep learning method to predict the progression of diseases using longitudinal imaging data with uneven time intervals, which requires no prior feature extraction.
1 code implementation • 10 Jul 2020 • Yuhui Ma, Huaying Hao, Huazhu Fu, Jiong Zhang, Jianlong Yang, Jiang Liu, Yalin Zheng, Yitian Zhao
To address these issues, for the first time in the field of retinal image analysis we construct a dedicated Retinal OCT-A SEgmentation dataset (ROSE), which consists of 229 OCT-A images with vessel annotations at either centerline-level or pixel level.
Ranked #1 on Retinal Vessel Segmentation on ROSE-1 DVC