1 code implementation • 23 Feb 2024 • Fengming Lin, Yan Xia, Michael MacRaild, Yash Deo, Haoran Dou, Qiongyao Liu, Nina Cheng, Nishant Ravikumar, Alejandro F. Frangi
The automated segmentation of cerebral aneurysms is pivotal for accurate diagnosis and treatment planning.
1 code implementation • 23 Feb 2024 • Fengming Lin, Yan Xia, Michael MacRaild, Yash Deo, Haoran Dou, Qiongyao Liu, Kun Wu, Nishant Ravikumar, Alejandro F. Frangi
Unsupervised domain adaptation (UDA) aims to align the labelled source distribution with the unlabelled target distribution to obtain domain-invariant predictive models.
no code implementations • 24 Aug 2023 • Yash Deo, Rodrigo Bonazzola, Haoran Dou, Yan Xia, Tianyou Wei, Nishant Ravikumar, Alejandro F. Frangi, Toni Lassila
We present an encoder-decoder model for synthesising segmentations of the main cerebral arteries in the circle of Willis (CoW) from only T2 MRI.
no code implementations • 13 Aug 2023 • Yash Deo, Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi, Toni Lassila
The Circle of Willis (CoW) is the part of cerebral vasculature responsible for delivering blood to the brain.
1 code implementation • 3 Jul 2023 • Luyi Han, Tianyu Zhang, Yunzhi Huang, Haoran Dou, Xin Wang, Yuan Gao, Chunyao Lu, Tan Tao, Ritse Mann
Multi-sequence MRI is valuable in clinical settings for reliable diagnosis and treatment prognosis, but some sequences may be unusable or missing for various reasons.
1 code implementation • 26 Jun 2023 • Haoran Dou, Ning Bi, Luyi Han, Yuhao Huang, Ritse Mann, Xin Yang, Dong Ni, Nishant Ravikumar, Alejandro F. Frangi, Yunzhi Huang
In this study, we construct a registration model based on the gradient surgery mechanism, named GSMorph, to achieve a hyperparameter-free balance on multiple losses.
no code implementations • 26 Jun 2023 • Haoran Dou, Nishant Ravikumar, Alejandro F. Frangi
The generation of virtual populations (VPs) of anatomy is essential for conducting in silico trials of medical devices.
no code implementations • 5 Jun 2023 • Yuhao Huang, Xin Yang, Xiaoqiong Huang, Xinrui Zhou, Haozhe Chi, Haoran Dou, Xindi Hu, Jian Wang, Xuedong Deng, Dong Ni
Second, we introduce a regularization technique that utilizes style interpolation consistency in the frequency space to encourage self-consistency in the logit space of the model output.
no code implementations • 4 Oct 2022 • Haoran Dou, Seppo Virtanen, Nishant Ravikumar, Alejandro F. Frangi
Specifically, we propose a generative shape compositional framework which comprises two components - a part-aware generative shape model which captures the variability in shape observed for each structure of interest in the training population; and a spatial composition network which assembles/composes the structures synthesised by the former into multi-part shape assemblies (viz.
no code implementations • 1 Jul 2022 • Yuhao Huang, Xin Yang, Xiaoqiong Huang, Jiamin Liang, Xinrui Zhou, Cheng Chen, Haoran Dou, Xindi Hu, Yan Cao, Dong Ni
Deep segmentation models often face the failure risks when the testing image presents unseen distributions.
no code implementations • 1 Jul 2022 • Yuxin Zou, Haoran Dou, Yuhao Huang, Xin Yang, Jikuan Qian, Chaojiong Zhen, Xiaodan Ji, Nishant Ravikumar, Guoqiang Chen, Weijun Huang, Alejandro F. Frangi, Dong Ni
First, we formulate SP localization in 3D US as a tangent-point-based problem in RL to restructure the action space and significantly reduce the search space.
1 code implementation • 30 Jun 2022 • Haoran Dou, Luyi Han, Yushuang He, Jun Xu, Nishant Ravikumar, Ritse Mann, Alejandro F. Frangi, Pew-Thian Yap, Yunzhi Huang
Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy.
no code implementations • 28 Oct 2021 • Luyi Han, Haoran Dou, Yunzhi Huang, Pew-Thian Yap
Unsupervised learning strategy is widely adopted by the deformable registration models due to the lack of ground truth of deformation fields.
no code implementations • 2 Aug 2021 • Yuhao Huang, Xin Yang, Yuxin Zou, Chaoyu Chen, Jian Wang, Haoran Dou, Nishant Ravikumar, Alejandro F Frangi, Jianqiao Zhou, Dong Ni
Weakly-supervised segmentation (WSS) can help reduce time-consuming and cumbersome manual annotation.
no code implementations • 22 May 2021 • Xin Yang, Yuhao Huang, Ruobing Huang, Haoran Dou, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Chaoyu Chen, Yuanji Zhang, Haixia Wang, Yi Xiong, Dong Ni
First, our proposed method is general and it can accurately localize multiple SPs in different challenging US datasets.
Multi-agent Reinforcement Learning Neural Architecture Search
1 code implementation • 26 Mar 2021 • Xin Yang, Haoran Dou, Ruobing Huang, Wufeng Xue, Yuhao Huang, Jikuan Qian, Yuanji Zhang, Huanjia Luo, Huizhi Guo, Tianfu Wang, Yi Xiong, Dong Ni
2D US has to perform scanning for each SP, which is time-consuming and operator-dependent.
no code implementations • 10 Oct 2020 • Haoming Li, Xin Yang, Jiamin Liang, Wenlong Shi, Chaoyu Chen, Haoran Dou, Rui Li, Rui Gao, Guangquan Zhou, Jinghui Fang, Xiaowen Liang, Ruobing Huang, Alejandro Frangi, Zhiyi Chen, Dong Ni
However, the lack of sharp boundaries in US images still remains an inherent challenge for segmentation.
no code implementations • 30 Jul 2020 • Yuhao Huang, Xin Yang, Rui Li, Jikuan Qian, Xiaoqiong Huang, Wenlong Shi, Haoran Dou, Chaoyu Chen, Yuanji Zhang, Huanjia Luo, Alejandro Frangi, Yi Xiong, Dong Ni
In this study, we propose a novel Multi-Agent Reinforcement Learning (MARL) framework to localize multiple uterine SPs in 3D US simultaneously.
Multi-agent Reinforcement Learning Neural Architecture Search
1 code implementation • 28 Apr 2020 • Xin Yang, Xu Wang, Yi Wang, Haoran Dou, Shengli Li, Huaxuan Wen, Yi Lin, Pheng-Ann Heng, Dong Ni
In this paper, we propose the first fully-automated solution to segment the whole fetal head in US volumes.
2 code implementations • 27 Apr 2020 • Haoran Dou, Davood Karimi, Caitlin K. Rollins, Cynthia M. Ortinau, Lana Vasung, Clemente Velasco-Annis, Abdelhakim Ouaalam, Xin Yang, Dong Ni, Ali Gholipour
Automatic segmentation of the cortical plate, on the other hand, is challenged by the relatively low resolution of the reconstructed fetal brain MRI scans compared to the thin structure of the cortical plate, partial voluming, and the wide range of variations in the morphology of the cortical plate as the brain matures during gestation.
no code implementations • 1 Apr 2020 • Jiamin Liang, Xin Yang, Haoming Li, Yi Wang, Manh The Van, Haoran Dou, Chaoyu Chen, Jinghui Fang, Xiaowen Liang, Zixin Mai, Guowen Zhu, Zhiyi Chen, Dong Ni
Efficiently synthesizing realistic, editable and high resolution US images can solve the problems.
no code implementations • 14 Feb 2020 • Zhendong Liu, Xin Yang, Rui Gao, Shengfeng Liu, Haoran Dou, Shuangchi He, Yuhao Huang, Yankai Huang, Huanjia Luo, Yuanji Zhang, Yi Xiong, Dong Ni
In this paper, we propose a novel and intuitive framework to remove the appearance shift, and hence improve the generalization ability of DNNs.
no code implementations • 5 Dec 2019 • Davood Karimi, Haoran Dou, Simon K. Warfield, Ali Gholipour
Then, we review studies that have dealt with label noise in deep learning for medical image analysis.
no code implementations • 11 Oct 2019 • Xin Yang, Wenlong Shi, Haoran Dou, Jikuan Qian, Yi Wang, Wufeng Xue, Shengli Li, Dong Ni, Pheng-Ann Heng
(i) This is the first work about 3D pose estimation of fetus in the literature.
1 code implementation • 10 Oct 2019 • Haoran Dou, Xin Yang, Jikuan Qian, Wufeng Xue, Hao Qin, Xu Wang, Lequan Yu, Shujun Wang, Yi Xiong, Pheng-Ann Heng, Dong Ni
In this study, we propose a novel reinforcement learning (RL) framework to automatically localize fetal brain standard planes in 3D US.
no code implementations • 31 Aug 2019 • Xu Wang, Xin Yang, Haoran Dou, Shengli Li, Pheng-Ann Heng, Dong Ni
In this paper, we propose an effective framework for simultaneous segmentation and landmark localization in prenatal ultrasound volumes.
1 code implementation • 3 Jul 2019 • Yi Wang, Haoran Dou, Xiao-Wei Hu, Lei Zhu, Xin Yang, Ming Xu, Jing Qin, Pheng-Ann Heng, Tianfu Wang, Dong Ni
Our attention module utilizes the attention mechanism to selectively leverage the multilevel features integrated from different layers to refine the features at each individual layer, suppressing the non-prostate noise at shallow layers of the CNN and increasing more prostate details into features at deep layers.