858 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Shanghai Artificial Intelligence LaboratoryCN102 papers
- University of Chinese Academy of SciencesCN77 papers
- Chinese Academy of SciencesCN73 papers
- Peking UniversityCN67 papers
- Tsinghua UniversityCN65 papers
- Institute of AutomationCN58 papers
- Shandong Institute of AutomationCN35 papers
- Shanghai Jiao Tong UniversityCN34 papers
- Beihang UniversityCN25 papers
- Fudan UniversityCN25 papers
- Center for Excellence in Brain Science and Intelligence TechnologyCN20 papers
- Chinese University of Hong KongHK19 papers
15 papers · 1 filter
Unsupervised Deformable Image Registration with Local-Global Attention and Image Decomposition
Zhengyong Huang, Xingwen Sun, Xuting Chang +5
Deformable image registration is a critical technology in medical image analysis, with broad applications in clinical practice such as disease diagnosis, multi-modal fusion, and su…
GAPNet: Granularity Attention Network with Anatomy-Prior-Constraint for Carotid Artery Segmentation
Lin Zhang, Chenggang Lu, Xin-yang Shi +4
Atherosclerosis is a chronic, progressive disease that primarily affects the arterial walls. It is one of the major causes of cardiovascular disease. Magnetic Resonance (MR) black-…
Spectral-wise Implicit Neural Representation for Hyperspectral Image Reconstruction
Huan Chen, Wangcai Zhao, Tingfa Xu +3
Coded Aperture Snapshot Spectral Imaging (CASSI) reconstruction aims to recover the 3D spatial-spectral signal from 2D measurement. Existing methods for reconstructing Hyperspectra…
A-Eval: A Benchmark for Cross-Dataset Evaluation of Abdominal Multi-Organ Segmentation
Ziyan Huang, Zhongying Deng, Jin Ye +11
Although deep learning have revolutionized abdominal multi-organ segmentation, models often struggle with generalization due to training on small, specific datasets. With the recen…
Classification of lung cancer subtypes on CT images with synthetic pathological priors
Wentao Zhu, Yuan Jin, Gege Ma +4
The accurate diagnosis on pathological subtypes for lung cancer is of significant importance for the follow-up treatments and prognosis managements. In this paper, we propose self-…
The Multi-modality Cell Segmentation Challenge: Towards Universal Solutions
Jun Ma, Ronald Xie, Shamini Ayyadhury +37
Cell segmentation is a critical step for quantitative single-cell analysis in microscopy images. Existing cell segmentation methods are often tailored to specific modalities or req…
RDFNet: Regional Dynamic FISTA-Net for Spectral Snapshot Compressive Imaging
Shiyun Zhou, Tingfa Xu, Shaocong Dong +1
Deep convolutional neural networks have recently shown promising results in compressive spectral reconstruction. Previous methods, however, usually adopt a single mapping function…
2D and 3D CT Radiomic Features Performance Comparison in Characterization of Gastric Cancer: A Multi-center Study
Lingwei Meng, Di Dong, Xin Chen +5
Objective: Radiomics, an emerging tool for medical image analysis, is potential towards precisely characterizing gastric cancer (GC). Whether using one-slice 2D annotation or whole…
PyMIC: A deep learning toolkit for annotation-efficient medical image segmentation
Guotai Wang, Xiangde Luo, Ran Gu +6
Background and Objective: Open-source deep learning toolkits are one of the driving forces for developing medical image segmentation models. Existing toolkits mainly focus on fully…
High-Frequency Space Diffusion Models for Accelerated MRI
Chentao Cao, Zhuo-Xu Cui, Yue Wang +5
Diffusion models with continuous stochastic differential equations (SDEs) have shown superior performances in image generation. It can serve as a deep generative prior to solving t…
A Dual Sensor Computational Camera for High Quality Dark Videography
Yuxiao Cheng, Runzhao Yang, Zhihong Zhang +2
Videos captured under low light conditions suffer from severe noise. A variety of efforts have been devoted to image/video noise suppression and made large progress. However, in ex…
WORD: A large scale dataset, benchmark and clinical applicable study for abdominal organ segmentation from CT image
Xiangde Luo, Wenjun Liao, Jianghong Xiao +7
Whole abdominal organ segmentation is important in diagnosing abdomen lesions, radiotherapy, and follow-up. However, oncologists' delineating all abdominal organs from 3D volumes i…
Polyp-PVT: Polyp Segmentation with Pyramid Vision Transformers
Bo Dong, Wenhai Wang, Deng-Ping Fan +3
Most polyp segmentation methods use CNNs as their backbone, leading to two key issues when exchanging information between the encoder and decoder: 1) taking into account the differ…
The Federated Tumor Segmentation (FeTS) Challenge
Sarthak Pati, Ujjwal Baid, Maximilian Zenk +29
This manuscript describes the first challenge on Federated Learning, namely the Federated Tumor Segmentation (FeTS) challenge 2021. International challenges have become the standar…
A Structure-Aware Relation Network for Thoracic Diseases Detection and Segmentation
Jie Lian, Jingyu Liu, Shu Zhang +4
Instance level detection and segmentation of thoracic diseases or abnormalities are crucial for automatic diagnosis in chest X-ray images. Leveraging on constant structure and dise…