Search Results for author: Guanyu Yang

Found 22 papers, 14 papers with code

Dynamic Snake Convolution based on Topological Geometric Constraints for Tubular Structure Segmentation

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.

Segmentation Specificity

XMorpher: Full Transformer for Deformable Medical Image Registration via Cross Attention

1 code implementation15 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.

Deformable Medical Image Registration Image Registration +2

Self-Supervised Speech Denoising Using Only Noisy Audio Signals

1 code implementation30 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.

Audio Denoising Denoising +1

Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training

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.

Geometric Matching Representation Learning

W-Net : One-Shot Arbitrary-StyleChinese Character Generationwith Deep Neural Networks

1 code implementation13 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.

NCAGC: A Neighborhood Contrast Framework for Attributed Graph Clustering

2 code implementations16 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.

Clustering Contrastive Learning +4

FFCNet: Fourier Transform-Based Frequency Learning and Complex Convolutional Network for Colon Disease Classification

1 code implementation4 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.

Partial Vessels Annotation-based Coronary Artery Segmentation with Self-training and Prototype Learning

1 code implementation10 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.

Coronary Artery Segmentation Segmentation +1

Knowledge Boosting: Rethinking Medical Contrastive Vision-Language Pre-Training

1 code implementation14 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.

Clinical Knowledge Representation Learning +1

Rebalanced Zero-shot Learning

1 code implementation13 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.

Zero-Shot Learning

Multiscale Low-Frequency Memory Network for Improved Feature Extraction in Convolutional Neural Networks

1 code implementation13 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.

Image Classification Image-to-Image Translation +1

MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation

2 code implementations10 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).

Image Segmentation Medical Image Segmentation +1

Efficient Legendre moment computation for grey level images

no code implementations12 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.

CSLNSpeech: solving extended speech separation problem with the help of Chinese sign language

1 code implementation21 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.

Self-Supervised Learning Speech Separation

Generative networks as inverse problems with fractional wavelet scattering networks

no code implementations28 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.

Image Generation

Deep Complementary Joint Model for Complex Scene Registration and Few-shot Segmentation on Medical Images

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.

Image Registration Medical Image Registration +1

EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation

no code implementations8 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.

Ensemble Learning Segmentation

Contrastive Re-localization and History Distillation in Federated CMR 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.

Federated Learning Image Segmentation +3

FedSODA: Federated Cross-assessment and Dynamic Aggregation for Histopathology Segmentation

no code implementations20 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.

Federated Learning Image Segmentation +2

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