1 code implementation • 27 Mar 2024 • Jiayu Huo, Xi Ouyang, Sébastien Ourselin, Rachel Sparks
Concretely, GMS employs a robust pre-trained vision foundation model to extract latent representations for images and corresponding ground truth masks, followed by a model that learns a mapping function from the image to the mask in the latent space.
1 code implementation • 2 Jul 2023 • Jiayu Huo, Yang Liu, Xi Ouyang, Alejandro Granados, Sebastien Ourselin, Rachel Sparks
In this paper, we propose a foreground harmonization framework (ARHNet) to tackle intensity disparities and make synthetic images look more realistic.
1 code implementation • 15 May 2023 • Sheng Wang, Zixu Zhuang, Xi Ouyang, Lichi Zhang, Zheren Li, Chong Ma, Tianming Liu, Dinggang Shen, Qian Wang
Then, we propose a novel augmentation method, i. e., FocusContrast, to learn from radiologists' gaze in diagnosis and generate contrastive views for medical images with guidance from radiologists' visual attention.
no code implementations • 20 Apr 2023 • Zheren Li, Zhiming Cui, Lichi Zhang, Sheng Wang, Chenjin Lei, Xi Ouyang, Dongdong Chen, Xiangyu Zhao, Yajia Gu, Zaiyi Liu, Chunling Liu, Dinggang Shen, Jie-Zhi Cheng
The training of an efficacious deep learning model requires large data with diverse styles and qualities.
1 code implementation • 14 Feb 2023 • Sheng Wang, Zihao Zhao, Xi Ouyang, Qian Wang, Dinggang Shen
Large language models (LLMs) have recently demonstrated their potential in clinical applications, providing valuable medical knowledge and advice.
no code implementations • 19 Jul 2022 • Zhenrong Shen, Xi Ouyang, Bin Xiao, Jie-Zhi Cheng, Qian Wang, Dinggang Shen
Moreover, we propose to synthesize nodule CXR images by controlling the disentangled nodule attributes for data augmentation, in order to better compensate for the nodules that are easily missed in the detection task.
1 code implementation • 6 Apr 2022 • Sheng Wang, Xi Ouyang, Tianming Liu, Qian Wang, Dinggang Shen
In this paper, we demonstrate that the eye movement of radiologists reading medical images can be a new form of supervision to train the DNN-based computer-aided diagnosis (CAD) system.
no code implementations • 12 Jan 2022 • Zixu Zhuang, Liping Si, Sheng Wang, Kai Xuan, Xi Ouyang, Yiqiang Zhan, Zhong Xue, Lichi Zhang, Dinggang Shen, Weiwu Yao, Qian Wang
Knee osteoarthritis (OA) is the most common osteoarthritis and a leading cause of disability.
1 code implementation • 23 Dec 2021 • Xi Ouyang, Srikrishna Karanam, Ziyan Wu, Terrence Chen, Jiayu Huo, Xiang Sean Zhou, Qian Wang, Jie-Zhi Cheng
However, doing this accurately will require a large amount of disease localization annotations by clinical experts, a task that is prohibitively expensive to accomplish for most applications.
1 code implementation • 21 Nov 2021 • Zheren Li, Zhiming Cui, Sheng Wang, Yuji Qi, Xi Ouyang, Qitian Chen, Yuezhi Yang, Zhong Xue, Dinggang Shen, Jie-Zhi Cheng
Specifically, the backbone network is firstly trained with a multi-style and multi-view unsupervised self-learning scheme for the embedding of invariant features to various vendor-styles.
no code implementations • 25 May 2020 • Sheng Wang, Jiayu Huo, Xi Ouyang, Jifei Che, Xuhua Ren, Zhong Xue, Qian Wang, Jie-Zhi Cheng
However, the image styles of different vendors are very distinctive, and there may exist domain gap among different vendors that could potentially compromise the universal applicability of one deep learning model.
1 code implementation • 19 May 2020 • Jiayu Huo, Liping Si, Xi Ouyang, Kai Xuan, Weiwu Yao, Zhong Xue, Qian Wang, Dinggang Shen, Lichi Zhang
With dual-consistency checking of the attention in the lesion classification and localization, the two networks can gradually optimize the attention distribution and improve the performance of each other, whereas the training relies on partially labeled data only and follows the semi-supervised manner.
no code implementations • 6 May 2020 • Xi Ouyang, Jiayu Huo, Liming Xia, Fei Shan, Jun Liu, Zhanhao Mo, Fuhua Yan, Zhongxiang Ding, Qi Yang, Bin Song, Feng Shi, Huan Yuan, Ying WEI, Xiaohuan Cao, Yaozong Gao, Dijia Wu, Qian Wang, Dinggang Shen
To this end, we develop a dual-sampling attention network to automatically diagnose COVID- 19 from the community acquired pneumonia (CAP) in chest computed tomography (CT).
2 code implementations • 5 Apr 2018 • Xi Ouyang, Yu Cheng, Yifan Jiang, Chun-Liang Li, Pan Zhou
The results show that our framework can smoothly synthesize pedestrians on background images of variations and different levels of details.
Ranked #2 on Scene Text Recognition on MSDA
no code implementations • 7 Nov 2017 • Chaoyun Zhang, Xi Ouyang, Paul Patras
Large-scale mobile traffic analytics is becoming essential to digital infrastructure provisioning, public transportation, events planning, and other domains.