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.
1 code implementation • ECCV 2020 • Ran Song, Wei zhang, Yitian Zhao, Yonghuai Liu
We present an unsupervised 3D deep learning framework based on a ubiquitously true proposition named by us view-object consistency as it states that a 3D object and its projected 2D views always belong to the same object class.
1 code implementation • 23 Aug 2022 • Jinkui Hao, Ting Shen, Xueli Zhu, Yonghuai Liu, Ardhendu Behera, Dan Zhang, Bang Chen, Jiang Liu, Jiong Zhang, Yitian Zhao
Automated detection of retinal structures, such as retinal vessels (RV), the foveal avascular zone (FAZ), and retinal vascular junctions (RVJ), are of great importance for understanding diseases of the eye and clinical decision-making.
1 code implementation • 25 Jul 2022 • Amrest Chinkamol, Vetit Kanjaras, Phattarapong Sawangjai, Yitian Zhao, Thapanun Sudhawiyangkul, Chantana Chantrapornchai, Cuntai Guan, Theerawit Wilaiprasitporn
In this work, we propose the application of the scribble-base weakly-supervised learning method to automate the pixel-level annotation.
Ranked #1 on Retinal Vessel Segmentation on ROSE-2
no code implementations • 25 Jul 2022 • Huaying Hao, Cong Xu, Dan Zhang, Qifeng Yan, Jiong Zhang, Yue Liu, Yitian Zhao
To be more specific, we first perform a simple degradation of the 3x3 mm2/high-resolution (HR) image to obtain the synthetic LR image.
1 code implementation • 9 Jun 2022 • Heng Li, Haofeng Liu, Huazhu Fu, Hai Shu, Yitian Zhao, Xiaoling Luo, Yan Hu, Jiang Liu
In this paper, to circumvent the strict deployment requirement, a structure-consistent restoration network (SCR-Net) for cataract fundus images is developed from synthesized data that shares an identical structure.
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).
1 code implementation • 15 Mar 2022 • Heng Li, Haofeng Liu, Yan Hu, Huazhu Fu, Yitian Zhao, Hanpei Miao, Jiang Liu
The restoration model is learned from the synthesized images and adapted to real cataract images.
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.
no code implementations • 24 Nov 2021 • Jialu Zhang, Qian Zhang, Jianfeng Ren, Yitian Zhao, Jiang Liu
Multi-label image classification is a fundamental but challenging task in computer vision.
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.
1 code implementation • 1 Jul 2021 • Yuhao Niu, Lin Gu, Yitian Zhao, Feng Lu
Though deep learning has shown successful performance in classifying the label and severity stage of certain diseases, most of them give few explanations on how to make predictions.
1 code implementation • CVPR 2021 • Ran Song, Wei zhang, Yitian Zhao, Yonghuai Liu, Paul L. Rosin
While mesh saliency aims to predict regional importance of 3D surfaces in agreement with human visual perception and is well researched in computer vision and graphics, latest work with eye-tracking experiments shows that state-of-the-art mesh saliency methods remain poor at predicting human fixations.
no code implementations • 26 May 2021 • Jiansheng Fang, Yanwu Xu, Yitian Zhao, Yuguang Yan, Junling Liu, Jiang Liu
By zeroing features of non-lung and heart regions in attention maps, we can effectively exploit their disease-specific cues in lung and heart regions.
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.
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
2 code implementations • 9 Jun 2020 • Jinkui Hao, Huazhu Fu, Yanwu Xu, Yan Hu, Fei Li, Xiulan Zhang, Jiang Liu, Yitian Zhao
We consider it to be the first work to detect angle-closure glaucoma by means of 3D representation.
no code implementations • 9 Jun 2020 • Huaying Hao, Huazhu Fu, Yanwu Xu, Jianlong Yang, Fei Li, Xiulan Zhang, Jiang Liu, Yitian Zhao
However, clinical diagnosis requires a more discriminating ACA three-class system (i. e., open, narrow, or synechiae angles) for the benefit of clinicians who seek better to understand the progression of the spectrum of angle-closure glaucoma types.
no code implementations • 28 Nov 2019 • Kang Zhou, Shenghua Gao, Jun Cheng, Zaiwang Gu, Huazhu Fu, Zhi Tu, Jianlong Yang, Yitian Zhao, Jiang Liu
With the development of convolutional neural network, deep learning has shown its success for retinal disease detection from optical coherence tomography (OCT) images.
no code implementations • 26 Oct 2019 • Lei Mou, Li Chen, Jun Cheng, Zaiwang Gu, Yitian Zhao, Jiang Liu
Many methods have been proposed for vessel detection.
no code implementations • 9 Aug 2019 • Hao Qiu, Zaiwang Gu, Lei Mou, Xiaoqian Mao, Liyang Fang, Yitian Zhao, Jiang Liu, Jun Cheng
The optic disc segmentation is an important step for retinal image-based disease diagnosis such as glaucoma.
no code implementations • 6 Aug 2019 • Tianyang Zhang, Huazhu Fu, Yitian Zhao, Jun Cheng, Mengjie Guo, Zaiwang Gu, Bing Yang, Yuting Xiao, Shenghua Gao, Jiang Liu
Generative Adversarial Networks (GANs) have the capability of synthesizing images, which have been successfully applied to medical image synthesis tasks.
no code implementations • 24 Jul 2019 • Xingjun Ma, Yuhao Niu, Lin Gu, Yisen Wang, Yitian Zhao, James Bailey, Feng Lu
This raises safety concerns about the deployment of these systems in clinical settings.
3 code implementations • 7 Mar 2019 • Zaiwang Gu, Jun Cheng, Huazhu Fu, Kang Zhou, Huaying Hao, Yitian Zhao, Tianyang Zhang, Shenghua Gao, Jiang Liu
In this paper, we propose a context encoder network (referred to as CE-Net) to capture more high-level information and preserve spatial information for 2D medical image segmentation.
Ranked #1 on Optic Disc Segmentation on Messidor