1 code implementation • ICCV 2023 • Yaolei Qi, Yuting He, Xiaoming Qi, Yuan Zhang, Guanyu Yang
In this work, we note the specificity of tubular structures and use this knowledge to guide our DSCNet to simultaneously enhance perception in three stages: feature extraction, feature fusion, and loss constraint.
1 code implementation • 15 Jun 2022 • Jiacheng Shi, Yuting He, Youyong Kong, Jean-Louis Coatrieux, Huazhong Shu, Guanyu Yang, Shuo Li
An effective backbone network is important to deep learning-based Deformable Medical Image Registration (DMIR), because it extracts and matches the features between two images to discover the mutual correspondence for fine registration.
1 code implementation • 30 Oct 2021 • Jiasong Wu, Qingchun Li, Guanyu Yang, Lei LI, Lotfi Senhadji, Huazhong Shu
The first module adopts a random audio sub-sampler on each noisy audio to generate training pairs.
1 code implementation • CVPR 2023 • Yuting He, Guanyu Yang, Rongjun Ge, Yang Chen, Jean-Louis Coatrieux, Boyu Wang, Shuo Li
We propose a novel visual similarity learning paradigm, Geometric Visual Similarity Learning, which embeds the prior of topological invariance into the measurement of the inter-image similarity for consistent representation of semantic regions.
1 code implementation • 13 Dec 2018 • Haochuan Jiang, Guanyu Yang, Kaizhu Huang, and Rui ZHANG
Due to the huge category number, the sophisticated com-binations of various strokes and radicals, and the free writing or print-ing styles, generating Chinese characters with diverse styles is alwaysconsidered as a difficult task.
2 code implementations • 16 Jun 2022 • Tong Wang, Guanyu Yang, Qijia He, Zhenquan Zhang, Junhua Wu
However, most existing methods 1) do not directly address the clustering task, since the representation learning and clustering process are separated; 2) depend too much on data augmentation, which greatly limits the capability of contrastive learning; 3) ignore the contrastive message for clustering tasks, which adversely degenerate the clustering results.
1 code implementation • 4 Jul 2022 • Kai-Ni Wang, Yuting He, Shuaishuai Zhuang, Juzheng Miao, Xiaopu He, Ping Zhou, Guanyu Yang, Guang-Quan Zhou, Shuo Li
Reliable automatic classification of colonoscopy images is of great significance in assessing the stage of colonic lesions and formulating appropriate treatment plans.
1 code implementation • 10 Jul 2023 • Zheng Zhang, XiaoLei Zhang, Yaolei Qi, Guanyu Yang
To this end, we propose partial vessels annotation (PVA) based on the challenges of coronary artery segmentation and clinical diagnostic characteristics.
1 code implementation • 14 Jul 2023 • Xiaofei Chen, Yuting He, Cheng Xue, Rongjun Ge, Shuo Li, Guanyu Yang
To address these issues, we propose the Knowledge-Boosting Contrastive Vision-Language Pre-training framework (KoBo), which integrates clinical knowledge into the learning of vision-language semantic consistency.
1 code implementation • 13 Oct 2022 • Zihan Ye, Guanyu Yang, Xiaobo Jin, Youfa Liu, Kaizhu Huang
Broadly speaking, present ZSL methods usually adopt class-level semantic labels and compare them with instance-level semantic predictions to infer unseen classes.
2 code implementations • 12 Dec 2023 • Weiguang Zhao, Guanyu Yang, Chaolong Yang, Chenru Jiang, Yuyao Yan, Rui Zhang, Kaizhu Huang
Such 2D diffusion to 3D objects proves vital in improving zero-shot classification for both ap-3os and op-3os.
1 code implementation • 13 Mar 2024 • Fuzhi Wu, Jiasong Wu, Youyong Kong, Chunfeng Yang, Guanyu Yang, Huazhong Shu, Guy Carrault, Lotfi Senhadji
Responding to these complexities, we introduce a novel framework, the Multiscale Low-Frequency Memory (MLFM) Network, with the goal to harness the full potential of CNNs while keeping their complexity unchanged.
2 code implementations • 10 May 2022 • Zhangfu Dong, Yuting He, Xiaoming Qi, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Guanyu Yang, Shuo Li
The nature of thick-slice scanning causes severe inter-slice discontinuities of 3D medical images, and the vanilla 2D/3D convolutional neural networks (CNNs) fail to represent sparse inter-slice information and dense intra-slice information in a balanced way, leading to severe underfitting to inter-slice features (for vanilla 2D CNNs) and overfitting to noise from long-range slices (for vanilla 3D CNNs).
no code implementations • 12 Mar 2014 • Guanyu Yang, Huazhong Shu, Christine Toumoulin, Guo-Niu Han, Limin M. Luo
Because their computation by a direct method is very time expensive, recent efforts have been devoted to the reduction of computational complexity.
no code implementations • 21 Feb 2019 • Xiahai Zhuang, Lei LI, Christian Payer, Darko Stern, Martin Urschler, Mattias P. Heinrich, Julien Oster, Chunliang Wang, Orjan Smedby, Cheng Bian, Xin Yang, Pheng-Ann Heng, Aliasghar Mortazi, Ulas Bagci, Guanyu Yang, Chenchen Sun, Gaetan Galisot, Jean-Yves Ramel, Thierry Brouard, Qianqian Tong, Weixin Si, Xiangyun Liao, Guodong Zeng, Zenglin Shi, Guoyan Zheng, Chengjia Wang, Tom MacGillivray, David Newby, Kawal Rhode, Sebastien Ourselin, Raad Mohiaddin, Jennifer Keegan, David Firmin, Guang Yang
This manuscript presents the methodologies and evaluation results for the WHS algorithms selected from the submissions to the Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, in conjunction with MICCAI 2017.
1 code implementation • 21 Jul 2020 • Jiasong Wu, Xuan Li, Taotao Li, Fanman Meng, Youyong Kong, Guanyu Yang, Lotfi Senhadji, Huazhong Shu
We design a general deep learning network for learning the combination of three modalities, audio, face, and sign language information, for better solving the speech separation problem.
no code implementations • 28 Jul 2020 • Jiasong Wu, Jing Zhang, Fuzhi Wu, Youyong Kong, Guanyu Yang, Lotfi Senhadji, Huazhong Shu
In order to solve or alleviate the synchronous training difficult problems of GANs and VAEs, recently, researchers propose Generative Scattering Networks (GSNs), which use wavelet scattering networks (ScatNets) as the encoder to obtain the features (or ScatNet embeddings) and convolutional neural networks (CNNs) as the decoder to generate the image.
no code implementations • ECCV 2020 • Yuting He, Tiantian Li, Guanyu Yang, Youyong Kong, Yang Chen, Huazhong Shu, Jean-Louis Coatrieux, Jean-Louis Dillenseger, Shuo Li
Deep learning-based medical image registration and segmentation joint models utilize the complementarity (augmentation data or weakly supervised data from registration, region constraints from segmentation) to bring mutual improvement in complex scene and few-shot situation.
no code implementations • 8 Jun 2021 • Yuting He, Rongjun Ge, Xiaoming Qi, Guanyu Yang, Yang Chen, Youyong Kong, Huazhong Shu, Jean-Louis Coatrieux, Shuo Li
3)We propose the adversarial weighted ensemble module which uses the trained discriminators to evaluate the quality of segmented structures, and normalizes these evaluation scores for the ensemble weights directed at the input image, thus enhancing the ensemble results.
no code implementations • 15 Aug 2021 • Song Wang, Yuting He, Youyong Kong, Xiaomei Zhu, Shaobo Zhang, Pengfei Shao, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Shuo Li, Guanyu Yang
We propose a novel weakly supervised learning framework, Cycle Prototype Network, for 3D renal compartment segmentation.
no code implementations • MICCAI 2022 2022 • Xiaoming Qi, Guanyu Yang, Yuting He, Wangyan Liu, Ali Islam, Shuo Li
In this work, a cross-center cross-sequence medical image segmentation FL framework (FedCRLD) is proposed for the first time to facilitate multi-center multi-sequence CMR segmentation.
no code implementations • 20 Dec 2023 • Yuan Zhang, Yaolei Qi, Xiaoming Qi, Lotfi Senhadji, Yongyue Wei, Feng Chen, Guanyu Yang
Federated learning (FL) for histopathology image segmentation involving multiple medical sites plays a crucial role in advancing the field of accurate disease diagnosis and treatment.