no code implementations • 21 May 2024 • Ziqin Lin, Heng Li, Zinan Li, Huazhu Fu, Jiang Liu
Furthermore, we discovered that overall fine-tuning is an effective adapter for LFM to mitigate the impact of dataset quality issues.
no code implementations • 12 May 2024 • Xinyuan Zhang, Jiang Liu, Zehui Xiong, Yudong Huang, Gaochang Xie, Ran Zhang
Specifically, with the deployment of the batching technique and model quantization on resource-limited edge devices, we formulate an inference model for transformer decoder-based LLMs.
1 code implementation • 2 May 2024 • Heng Li, Haojin Li, Jianyu Chen, Zhongxi Qiu, Huazhu Fu, Lidai Wang, Yan Hu, Jiang Liu
To tackle domain shifts in data-scarce medical scenarios, we propose a Random frequency filtering enabled Single-source Domain Generalization algorithm (RaffeSDG), which promises robust out-of-domain inference with segmentation models trained on a single-source domain.
no code implementations • 21 Apr 2024 • Haoyu Zheng, Wenqiao Zhang, Yaoke Wang, Hao Zhou, Jiang Liu, Juncheng Li, Zheqi Lv, Siliang Tang, Yueting Zhuang
Revolutionary advancements in text-to-image models have unlocked new dimensions for sophisticated content creation, e. g., text-conditioned image editing, allowing us to edit the diverse images that convey highly complex visual concepts according to the textual guidance.
no code implementations • 25 Mar 2024 • Qiushi Nie, Xiaoqing Zhang, Yan Hu, Mingdao Gong, Jiang Liu
Medical image registration is vital for disease diagnosis and treatment with its ability to merge diverse information of images, which may be captured under different times, angles, or modalities.
1 code implementation • 20 Mar 2024 • Wenqiao Zhang, Tianwei Lin, Jiang Liu, Fangxun Shu, Haoyuan Li, Lei Zhang, He Wanggui, Hao Zhou, Zheqi Lv, Hao Jiang, Juncheng Li, Siliang Tang, Yueting Zhuang
Recent advancements indicate that scaling up Multimodal Large Language Models (MLLMs) effectively enhances performance on downstream multimodal tasks.
Ranked #77 on Visual Question Answering on MM-Vet
no code implementations • 5 Mar 2024 • Chenqiang Gao, Chuandong Liu, Jun Shu, Fangcen Liu, Jiang Liu, Luyu Yang, Xinbo Gao, Deyu Meng
Current state-of-the-art (SOTA) 3D object detection methods often require a large amount of 3D bounding box annotations for training.
no code implementations • 1 Mar 2024 • Zexin Feng, Na Zeng, Jiansheng Fang, Xingyue Wang, Xiaoxi Lu, Heng Meng, Jiang Liu
Convolutional neural networks (CNNs) have long been the paradigm of choice for robust medical image processing (MIP).
1 code implementation • 20 Feb 2024 • Wenjun Hou, Yi Cheng, Kaishuai Xu, Yan Hu, Wenjie Li, Jiang Liu
Previous research on radiology report generation has made significant progress in terms of increasing the clinical accuracy of generated reports.
no code implementations • 23 Dec 2023 • Jialu Zhang, Xiaoying Yang, Wentao He, Jianfeng Ren, Qian Zhang, Titian Zhao, Ruibin Bai, Xiangjian He, Jiang Liu
A set of rewards measuring the localization accuracy, the accuracy of predicted labels, and the scale consistency among nearby patches are designed in the agent to guide the scale optimization.
no code implementations • 20 Dec 2023 • Haili Ye, Xiaoqing Zhang, Yan Hu, Huazhu Fu, Jiang Liu
Based on this, we propose a novel Vessel-like Structure Rehabilitation Network (VSR-Net) to rehabilitate subsection ruptures and improve the model calibration based on coarse vessel-like structure segmentation results.
1 code implementation • 3 Dec 2023 • Heng Li, Ziqin Lin, Zhongxi Qiu, Zinan Li, Huazhu Fu, Yan Hu, Jiang Liu
Additionally, a pseudo-label picker is developed to boost the knowledge distillation of enhancement tasks.
no code implementations • 27 Nov 2023 • Jiang Liu, Chen Wei, Yuxiang Guo, Heng Yu, Alan Yuille, Soheil Feizi, Chun Pong Lau, Rama Chellappa
We propose Instruct2Attack (I2A), a language-guided semantic attack that generates semantically meaningful perturbations according to free-form language instructions.
no code implementations • 27 Nov 2023 • Yuxiang Guo, Anshul Shah, Jiang Liu, Ayush Gupta, Rama Chellappa, Cheng Peng
Gait recognition holds the promise to robustly identify subjects based on walking patterns instead of appearance information.
no code implementations • 16 Nov 2023 • Aniket Roy, Maiterya Suin, Anshul Shah, Ketul Shah, Jiang Liu, Rama Chellappa
Diffusion models have advanced generative AI significantly in terms of editing and creating naturalistic images.
no code implementations • 14 Nov 2023 • Hang Yin, Kuang-Hung Liu, Mengying Sun, Yuxin Chen, Buyun Zhang, Jiang Liu, Vivek Sehgal, Rudresh Rajnikant Panchal, Eugen Hotaj, Xi Liu, Daifeng Guo, Jamey Zhang, Zhou Wang, Shali Jiang, Huayu Li, Zhengxing Chen, Wen-Yen Chen, Jiyan Yang, Wei Wen
The large scale of models and tight production schedule requires AutoML to outperform human baselines by only using a small number of model evaluation trials (around 100).
no code implementations • 14 Nov 2023 • Wei Wen, Kuang-Hung Liu, Igor Fedorov, Xin Zhang, Hang Yin, Weiwei Chu, Kaveh Hassani, Mengying Sun, Jiang Liu, Xu Wang, Lin Jiang, Yuxin Chen, Buyun Zhang, Xi Liu, Dehua Cheng, Zhengxing Chen, Guang Zhao, Fangqiu Han, Jiyan Yang, Yuchen Hao, Liang Xiong, Wen-Yen Chen
In industry system, such as ranking system in Meta, it is unclear whether NAS algorithms from the literature can outperform production baselines because of: (1) scale - Meta ranking systems serve billions of users, (2) strong baselines - the baselines are production models optimized by hundreds to thousands of world-class engineers for years since the rise of deep learning, (3) dynamic baselines - engineers may have established new and stronger baselines during NAS search, and (4) efficiency - the search pipeline must yield results quickly in alignment with the productionization life cycle.
no code implementations • 14 Nov 2023 • Hongyang Jiang, Mengdi Gao, Zirong Liu, Chen Tang, Xiaoqing Zhang, Shuai Jiang, Wu Yuan, Jiang Liu
In this work, we propose a human-in-the-loop, label-free early DR diagnosis framework called GlanceSeg, based on SAM.
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.
1 code implementation • 21 Oct 2023 • Wenjun Hou, Yi Cheng, Kaishuai Xu, Wenjie Li, Jiang Liu
It then combines the historical records, spatiotemporal information, and radiographs for report generation, where a disease progression graph and dynamic progression reasoning mechanism are devised to accurately select the attributes of each observation and progression.
no code implementations • 5 Oct 2023 • Luoying Hao, Yan Hu, Wenjun Lin, Qun Wang, Heng Li, Huazhu Fu, Jinming Duan, Jiang Liu
In this paper, to accurately detect fine-grained actions that happen at every moment, we propose an anchor-context action detection network (ACTNet), including an anchor-context detection (ACD) module and a class conditional diffusion (CCD) module, to answer the following questions: 1) where the actions happen; 2) what actions are; 3) how confidence predictions are.
1 code implementation • 17 Sep 2023 • Xiaoqing Zhang, Jilu Zhao, Yan Li, Hao Wu, Xiangtian Zhou, Jiang Liu
Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters.
no code implementations • 12 Sep 2023 • Han Su, Jiyu Zhu, Shenghua Feng, Yunjun Bai, Bin Gu, Jiang Liu, Mengfei Yang, Naijun Zhan
A reset controller plays a crucial role in designing hybrid systems.
no code implementations • 12 Sep 2023 • Jiang Liu, Han Su, Yunjun Bai, Bin Gu, Bai Xue, Mengfei Yang, Naijun Zhan
Controller synthesis, including reset controller, feedback controller, and switching logic controller, provides an essential mechanism to guarantee the correctness and reliability of hybrid systems in a correct-by-construction manner.
1 code implementation • 6 Sep 2023 • Mengjuan Liu, Chenyang Liu, Yunfan Yang, Jiang Liu, Mohan Jing
In this paper, we first build an open-domain dialogue model based on the pre-trained language model (i. e., GPT-2).
2 code implementations • 2 Sep 2023 • Heng Li, Haofeng Liu, Huazhu Fu, Yanwu Xu, Hui Shu, Ke Niu, Yan Hu, Jiang Liu
Fundus photography is prone to suffer from image quality degradation that impacts clinical examination performed by ophthalmologists or intelligent systems.
no code implementations • 29 Aug 2023 • Jiang Liu, Wei Dai
Given the prevalence of rolling bearing fault diagnosis as a practical issue across various working conditions, the limited availability of samples compounds the challenge.
1 code implementation • 18 Jul 2023 • Heng Li, Haojin Li, Wei Zhao, Huazhu Fu, Xiuyun Su, Yan Hu, Jiang Liu
Consequently, domain generalization (DG) is developed to boost the performance of segmentation models on unseen domains.
no code implementations • 2 Jul 2023 • Wei Dai, Jiang Liu, Lanhao Wang
Concretely, a cloud feature extraction method is first developed by using a backward cloud generator of normal cloud model to mine the uncertainty of fault information.
no code implementations • 16 Jun 2023 • Hongyang Jiang, Mengdi Gao, Yan Hu, Qiushi Ren, Zhaoheng Xie, Jiang Liu
Therefore, in this work, we innovatively devise noise-robust training approach to mitigate the adverse effects of noisy labels in medical image classification.
1 code implementation • 10 Jun 2023 • Wenjun Hou, Kaishuai Xu, Yi Cheng, Wenjie Li, Jiang Liu
This paper explores the task of radiology report generation, which aims at generating free-text descriptions for a set of radiographs.
no code implementations • 6 Jun 2023 • Jiang Liu, Hao Fei, Fei Li, Jingye Li, Bobo Li, Liang Zhao, Chong Teng, Donghong Ji
Few-shot named entity recognition (NER) exploits limited annotated instances to identify named mentions.
no code implementations • 30 May 2023 • Yinglin Zhang, Ruiling Xi, Huazhu Fu, Dave Towey, Ruibin Bai, Risa Higashita, Jiang Liu
Second, we extract the uncertainty under different scales and propose the multi-scale uncertainty-aware (MSUA) fusion module to integrate structure contexts from hierarchical predictions, strengthening the final prediction.
no code implementations • 25 May 2023 • Chenglin Yao, Jianfeng Ren, Ruibin Bai, Heshan Du, Jiang Liu, Xudong Jiang
Detecting 3D mask attacks to a face recognition system is challenging.
1 code implementation • 23 May 2023 • Jiang Liu, Chun Pong Lau, Rama Chellappa
In this work, we ask: can diffusion models be used to generate adversarial examples to improve both visual quality and attack performance?
no code implementations • 22 May 2023 • Chun Pong Lau, Jiang Liu, Rama Chellappa
In this paper, we propose Attribute Guided Encryption with Facial Texture Masking (AGE-FTM) that performs a dual manifold adversarial attack on FR systems to achieve both good visual quality and high black box attack success rates.
1 code implementation • 26 Apr 2023 • Zhongxi Qiu, Yan Hu, Heng Li, Jiang Liu
Based on Segment Anything (SAM), we propose a simple but effective learnable prompt layer suitable for multiple target segmentation in ophthalmology multi-modal images, named Learnable Ophthalmology Segment Anything (SAM).
no code implementations • 25 Apr 2023 • Hongyang Jiang, Jingqi Huang, Chen Tang, Xiaoqing Zhang, Mengdi Gao, Jiang Liu
Concretely, the HITL CAD system was implemented on the multiple instance learning (MIL), where eye-tracking gaze maps were beneficial to cherry-pick diagnosis-related instances.
no code implementations • 3 Mar 2023 • Xiaoqing Zhang, Zunjie Xiao, Xiao Wu, Yanlin Chen, Jilu Zhao, Yan Hu, Jiang Liu
Spatial attention mechanism has been widely incorporated into deep neural networks (DNNs), significantly lifting the performance in computer vision tasks via long-range dependency modeling.
1 code implementation • CVPR 2023 • Jiang Liu, Hui Ding, Zhaowei Cai, Yuting Zhang, Ravi Kumar Satzoda, Vijay Mahadevan, R. Manmatha
In this work, instead of directly predicting the pixel-level segmentation masks, the problem of referring image segmentation is formulated as sequential polygon generation, and the predicted polygons can be later converted into segmentation masks.
Ranked #1 on Referring Expression Segmentation on ReferIt (using extra training data)
no code implementations • 17 Nov 2022 • Jiayi Zhang, Xiaoshan Chen, Zhongxi Qiu, Mingming Yang, Yan Hu, Jiang Liu
Specifically, we propose a fusion module named Multi-scale Attention Fusion (MAF) module for our dual-stream framework to effectively integrate features of the two tasks.
1 code implementation • 1 Nov 2022 • Jiang Liu, Donghong Ji, Jingye Li, Dongdong Xie, Chong Teng, Liang Zhao, Fei Li
Concretely, we construct tag representations and embed them into TREM, so that TREM can treat tag and word representations as queries/keys/values and utilize self-attention to model their relationships.
1 code implementation • 18 Oct 2022 • Haofeng Liu, Heng Li, Huazhu Fu, Ruoxiu Xiao, Yunshu Gao, Yan Hu, Jiang Liu
For boosting the clinical deployment of fundus image enhancement, this paper proposes the pyramid constraint to develop a degradation-invariant enhancement network (PCE-Net), which mitigates the demand for clinical data and stably enhances unknown data.
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 • 28 Jul 2022 • Yan Hu, Zhongxi Qiu, Dan Zeng, Li Jiang, Chen Lin, Jiang Liu
Vascular segmentation extracts blood vessels from images and serves as the basis for diagnosing various diseases, like ophthalmic diseases.
no code implementations • 23 Jun 2022 • Jiansheng Fang, Anwei Li, Pu-Yun OuYang, Jiajian Li, Jingwen Wang, Hongbo Liu, Fang-Yun Xie, Jiang Liu
We design a deep multimodal survival network (MSN) with two feature extractors to learn discriminative features from multimodal data.
3 code implementations • 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 • 7 Jun 2022 • Jiansheng Fang, Jingwen Wang, Anwei Li, Yuguang Yan, Yonghe Hou, Chao Song, Hongbo Liu, Jiang Liu
In the management of lung nodules, we are desirable to predict nodule evolution in terms of its diameter variation on Computed Tomography (CT) scans and then provide a follow-up recommendation according to the predicted result of the growing trend of the nodule.
no code implementations • 25 May 2022 • Tianyang Zhang, Shaoming Zheng, Jun Cheng, Xi Jia, Joseph Bartlett, Xinxing Cheng, Huazhu Fu, Zhaowen Qiu, Jiang Liu, Jinming Duan
It consists of a spatial transformation block followed by an intensity distribution rendering module.
no code implementations • 28 Apr 2022 • Jiang Liu, Srivathsa Pasumarthi, Ben Duffy, Enhao Gong, Keshav Datta, Greg Zaharchuk
In this work, we formulate missing data imputation as a sequence-to-sequence learning problem and propose a multi-contrast multi-scale Transformer (MMT), which can take any subset of input contrasts and synthesize those that are missing.
2 code implementations • 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 • 10 Feb 2022 • Hao Jiang, Yanning Zhou, Yi Lin, Ronald CK Chan, Jiang Liu, Hao Chen
Computational cytology is a critical, rapid-developing, yet challenging topic in the field of medical image computing which analyzes the digitized cytology image by computer-aided technologies for cancer screening.
no code implementations • CVPR 2022 • Chuandong Liu, Chenqiang Gao, Fangcen Liu, Jiang Liu, Deyu Meng, Xinbo Gao
In the meantime, we design a reliable background mining module and a point cloud filling data augmentation strategy to generate the confident data for iteratively learning with reliable supervision.
1 code implementation • 19 Dec 2021 • Jingye Li, Hao Fei, Jiang Liu, Shengqiong Wu, Meishan Zhang, Chong Teng, Donghong Ji, Fei Li
So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka.
Ranked #2 on Chinese Named Entity Recognition on OntoNotes 4
no code implementations • 12 Dec 2021 • Chun Pong Lau, Jiang Liu, Hossein Souri, Wei-An Lin, Soheil Feizi, Rama Chellappa
Under JSTM, we develop novel adversarial attacks and defenses.
no code implementations • 9 Dec 2021 • Jiang Liu, Chun Pong Lau, Hossein Souri, Soheil Feizi, Rama Chellappa
In other words, we can make a weak model more robust with the help of a strong teacher model.
1 code implementation • CVPR 2022 • Jiang Liu, Alexander Levine, Chun Pong Lau, Rama Chellappa, Soheil Feizi
In addition, we design a robust shape completion algorithm, which is guaranteed to remove the entire patch from the images if the outputs of the patch segmenter are within a certain Hamming distance of the ground-truth patch masks.
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.
no code implementations • 5 Oct 2021 • Kang Zhou, Jing Li, Weixin Luo, Zhengxin Li, Jianlong Yang, Huazhu Fu, Jun Cheng, Jiang Liu, Shenghua Gao
To mitigate this problem, in this paper, we propose a novel Proxy-bridged Image Reconstruction Network (ProxyAno) for anomaly detection in medical images.
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 • 21 May 2021 • Yinglin Zhang, Risa Higashita, Huazhu Fu, Yanwu Xu, Yang Zhang, Haofeng Liu, Jian Zhang, Jiang Liu
Corneal endothelial cell segmentation plays a vital role inquantifying clinical indicators such as cell density, coefficient of variation, and hexagonality.
1 code implementation • 19 May 2021 • Jiansheng Fang, Huazhu Fu, Dan Zeng, Xiao Yan, Yuguang Yan, Jiang Liu
When encountering a dubious diagnostic case, medical instance retrieval can help radiologists make evidence-based diagnoses by finding images containing instances similar to a query case from a large image database.
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 • 29 Jan 2021 • Jiansheng Fang, Huazhu Fu, Jiang Liu
The triplet cross-entropy loss can help to map the classification information of images and similarity between images into the hash codes.
no code implementations • 9 Dec 2020 • Xiaoqing Zhang, Yan Hu, Zunjie Xiao, Jiansheng Fang, Risa Higashita, Jiang Liu
This survey provides a comprehensive survey of recent advances in machine learning techniques for cataract classification/grading based on ophthalmic images.
1 code implementation • 7 Dec 2020 • Jiansheng Fang, Yanwu Xu, Xiaoqing Zhang, Yan Hu, Jiang Liu
The different grades or classes of ophthalmic images may be share similar overall performance but have subtle differences that can be differentiated by mining salient regions.
1 code implementation • 7 Dec 2020 • Jiansheng Fang, Xiaoqing Zhang, Yan Hu, Yanwu Xu, Ming Yang, Jiang Liu
Latent Factor Model (LFM) is one of the most successful methods for Collaborative filtering (CF) in the recommendation system, in which both users and items are projected into a joint latent factor space.
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 • ECCV 2020 • Kang Zhou, Yuting Xiao, Jianlong Yang, Jun Cheng, Wen Liu, Weixin Luo, Zaiwang Gu, Jiang Liu, Shenghua Gao
In the end, we further utilize the reconstructed image to extract the structure and measure the difference between structure extracted from original and the reconstructed image.
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 • 5 May 2020 • Huazhu Fu, Fei Li, Xu sun, Xingxing Cao, Jingan Liao, Jose Ignacio Orlando, Xing Tao, Yuexiang Li, Shihao Zhang, Mingkui Tan, Chenglang Yuan, Cheng Bian, Ruitao Xie, Jiongcheng Li, Xiaomeng Li, Jing Wang, Le Geng, Panming Li, Huaying Hao, Jiang Liu, Yan Kong, Yongyong Ren, Hrvoje Bogunovic, Xiulan Zhang, Yanwu Xu
To address this, we organized the Angle closure Glaucoma Evaluation challenge (AGE), held in conjunction with MICCAI 2019.
no code implementations • 31 Jan 2020 • Chuang Wang, Ruimin Hu, Min Hu, Jiang Liu, Ting Ren, Shan He, Ming Jiang, Jing Miao
And we validate our method on the Aff-Wild2 datasets released by the Challenge.
Facial Expression Recognition Facial Expression Recognition (FER)
no code implementations • 15 Jan 2020 • Shaoming Zheng, Tianyang Zhang, Jiawei Zhuang, Hao Wang, Jiang Liu
In this paper, we propose a novel two-stream Meticulous-Processing Network (MP-Net) for tackling this problem.
no code implementations • 11 Dec 2019 • Huihong Zhang, Jianlong Yang, Kang Zhou, Zhenjie Chai, Jun Cheng, Shenghua Gao, Jiang Liu
Firstly, our method trains a biomarker prediction network to learn the features of the biomarker.
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 • 8 Oct 2019 • Henry H. Yu, Jiang Liu, Hao Sun, Ziwen Wang, Haotian Zhang
Image pairing is an important research task in the field of computer vision.
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.
4 code implementations • 10 Jul 2019 • Huazhu Fu, Boyang Wang, Jianbing Shen, Shanshan Cui, Yanwu Xu, Jiang Liu, Ling Shao
Retinal image quality assessment (RIQA) is essential for controlling the quality of retinal imaging and guaranteeing the reliability of diagnoses by ophthalmologists or automated analysis systems.
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
no code implementations • 10 Feb 2019 • Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Mani Baskaran, Meenakshi Mahesh, Tin Aung, Jiang Liu
A Multi-Level Deep Network (MLDN) is proposed to formulate this learning, which utilizes three particular AS-OCT regions based on clinical priors: the global anterior segment structure, local iris region, and anterior chamber angle (ACA) patch.
no code implementations • 10 Sep 2018 • Huazhu Fu, Yanwu Xu, Stephen Lin, Damon Wing Kee Wong, Baskaran Mani, Meenakshi Mahesh, Tin Aung, Jiang Liu
A major cause of irreversible visual impairment is angle-closure glaucoma, which can be screened through imagery from Anterior Segment Optical Coherence Tomography (AS-OCT).
no code implementations • 31 Aug 2018 • Kang Zhou, Zaiwang Gu, Wen Liu, Weixin Luo, Jun Cheng, Shenghua Gao, Jiang Liu
To considering the relationships of images with different stages, we propose a \textbf{Multi-Task} learning strategy which predicts the label with both classification and regression.
3 code implementations • 19 May 2018 • Huazhu Fu, Jun Cheng, Yanwu Xu, Changqing Zhang, Damon Wing Kee Wong, Jiang Liu, Xiaochun Cao
Specifically, a novel Disc-aware Ensemble Network (DENet) for automatic glaucoma screening is proposed, which integrates the deep hierarchical context of the global fundus image and the local optic disc region.
no code implementations • 17 May 2018 • Jun Cheng, Zhengguo Li, Zaiwang Gu, Huazhu Fu, Damon Wing Kee Wong, Jiang Liu
It often obscures the details in the retinal images and posts challenges in retinal image processing and analysing tasks.
3 code implementations • 3 Jan 2018 • Huazhu Fu, Jun Cheng, Yanwu Xu, Damon Wing Kee Wong, Jiang Liu, Xiaochun Cao
The proposed M-Net mainly consists of multi-scale input layer, U-shape convolutional network, side-output layer, and multi-label loss function.
Ranked #4 on Optic Disc Segmentation on REFUGE
1 code implementation • CVPR 2018 • Jiang Liu, Chenqiang Gao, Deyu Meng, Alexander G. Hauptmann
DecideNet starts with estimating the crowd density by generating detection and regression based density maps separately.
Ranked #10 on Crowd Counting on WorldExpo’10
no code implementations • 7 Mar 2016 • Lan Wang, Chenqiang Gao, Jiang Liu, Deyu Meng
Detecting complex events in a large video collection crawled from video websites is a challenging task.
no code implementations • CVPR 2015 • Huazhu Fu, Dong Xu, Stephen Lin, Jiang Liu
We present an object-based co-segmentation method that takes advantage of depth data and is able to correctly handle noisy images in which the common foreground object is missing.
no code implementations • CVPR 2015 • Jimmy Addison Lee, Jun Cheng, Beng Hai Lee, Ee Ping Ong, Guozhen Xu, Damon Wing Kee Wong, Jiang Liu, Augustinus Laude, Tock Han Lim
These customized step patterns are robust to non-linear intensity changes, which are well-suited for multimodal retinal image registration.