187 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Fudan UniversityCN59 papers
- Frontiers Center for Brain Science of the Ministry of EducationCN8 papers
- Rensselaer Polytechnic InstituteUS7 papers
- Shanghai Jiao Tong UniversityCN7 papers
- Chinese Academy of SciencesCN6 papers
- Sichuan UniversityCN6 papers
- Tsinghua UniversityCN5 papers
- Chongqing Normal UniversityCN4 papers
- East China Normal UniversityCN4 papers
- Huashan HospitalCN4 papers
- Shanxi UniversityCN4 papers
- Humboldt-Universität zu BerlinDE3 papers
82 papers
A Language-Guided Multimodal Foundation Model for Zero-Shot and Multi-Task Brain Signal Analysis
Mingzhi Chen, Yiyu Gui, Guibo Luo +1
Brain signal analysis is essential for both neuroscience research and clinical diagnostics, yet current approaches face critical limitations. End-to-end models require task-specifi…
Mid-Infrared Single-Photon Compressive Spectroscopy
Ben Sun, Kun Huang, Huijie Ma +7
Sensitive mid-infrared (MIR) spectroscopy plays an indispensable role in various photon-starved conditions. However, the detection sensitivity of conventional MIR spectrometers is…
High-speed mid-infrared imaging via nonlinear multiplexed detection
Ruiyang Qin, Kun Huang, Min Peng +4
High-speed mid-infrared (MIR) videography constitutes an enabling tool to monitor and analyze various dynamics in scientific research and industrial applications, such as combustio…
Mid-infrared single-photon computational temporal ghost imaging
Wen Zhang, Kun Huang, Xu Wang +4
The capture of transient optical waveforms is critical to reveal dynamical phenomena in various fields. However, fast and sensitive mid-infrared (MIR) measurements are typically li…
Infrared Single-Pixel Hyperspectral Imaging via Spatial-Temporal Multiplexing
Ben Sun, Kun Huang, Zhibin Zhao +3
Near-infrared (NIR) hyperspectral imaging is widely used to reveal morphological and chemical information. However, conventional spectral imagers usually rely on costly focal plane…
IR-Flow: Bridging Discriminative and Generative Image Restoration via Rectified Flow
Zihao Fan, Xin Lu, Jie Xiao +3
In image restoration, single-step discriminative mappings often lack fine details via expectation learning, whereas generative paradigms suffer from inefficient multi-step sampling…
Uncertainty-Supervised Interpretable and Robust Evidential Segmentation
Yuzhu Li, An Sui, Fuping Wu +1
Uncertainty estimation has been widely studied in medical image segmentation as a tool to provide reliability, particularly in deep learning approaches. However, previous methods g…
Extreme Cardiac MRI Analysis under Respiratory Motion: Results of the CMRxMotion Challenge
Kang Wang, Chen Qin, Zhang Shi +46
Deep learning models have achieved state-of-the-art performance in automated Cardiac Magnetic Resonance (CMR) analysis. However, the efficacy of these models is highly dependent on…
DTBIA: An Immersive Visual Analytics System for Brain-Inspired Research
Jun-Hsiang Yao, Mingzheng Li, Jiayi Liu +6
The Digital Twin Brain (DTB) is an advanced artificial intelligence framework that integrates spiking neurons to simulate complex cognitive functions and collaborative behaviors. F…
Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts
Lisa Hemforth, Baptiste Couvy-Duchesne, Kevin De Matos +34
Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population.…
HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation
Tao Chen, Chenhui Wang, Zhihao Chen +2
Medical image segmentation has been significantly advanced with the rapid development of deep learning (DL) techniques. Existing DL-based segmentation models are typically discrimi…
Towards Dynamic Trend Filtering through Trend Point Detection with Reinforcement Learning
Jihyeon Seong, Sekwang Oh, Jaesik Choi
Trend filtering simplifies complex time series data by applying smoothness to filter out noise while emphasizing proximity to the original data. However, existing trend filtering m…
Image-Text-Image Knowledge Transfer for Lifelong Person Re-Identification with Hybrid Clothing States
Qizao Wang, Xuelin Qian, Bin Li +2
With the continuous expansion of intelligent surveillance networks, lifelong person re-identification (LReID) has received widespread attention, pursuing the need of self-evolution…
Towards free-response paradigm: a theory on decision-making in spiking neural networks
Zhichao Zhu, Yang Qi, Wenlian Lu +3
The energy-efficient and brain-like information processing abilities of Spiking Neural Networks (SNNs) have attracted considerable attention, establishing them as a crucial element…
Evolutionary Preference Sampling for Pareto Set Learning
Rongguang Ye, Longcan Chen, Jinyuan Zhang +1
Recently, Pareto Set Learning (PSL) has been proposed for learning the entire Pareto set using a neural network. PSL employs preference vectors to scalarize multiple objectives, fa…
HOPE: Hybrid-granularity Ordinal Prototype Learning for Progression Prediction of Mild Cognitive Impairment
Chenhui Wang, Yiming Lei, Tao Chen +3
Mild cognitive impairment (MCI) is often at high risk of progression to Alzheimer's disease (AD). Existing works to identify the progressive MCI (pMCI) typically require MCI subtyp…
Quantifying energy landscape of high-dimensional oscillatory systems by diffusion decomposition
Shirui Bian, Ruisong Zhou, Wei Lin +1
High-dimensional networks producing oscillatory dynamics are ubiquitous in biological systems. Unravelling the mechanism of oscillatory dynamics in biological networks with stochas…
Bayesian Unsupervised Disentanglement of Anatomy and Geometry for Deep Groupwise Image Registration
Xinzhe Luo, Xin Wang, Linda Shapiro +3
This article presents a general Bayesian learning framework for multi-modal groupwise image registration. The method builds on probabilistic modelling of the image generative proce…
IQAGPT: Image Quality Assessment with Vision-language and ChatGPT Models
Zhihao Chen, Bin Hu, Chuang Niu +4
Large language models (LLMs), such as ChatGPT, have demonstrated impressive capabilities in various tasks and attracted an increasing interest as a natural language interface acros…
High-resolution myelin-water fraction and quantitative relaxation mapping using 3D ViSTa-MR fingerprinting
Congyu Liao, Xiaozhi Cao, Siddharth Srinivasan Iyer +14
Purpose: This study aims to develop a high-resolution whole-brain multi-parametric quantitative MRI approach for simultaneous mapping of myelin-water fraction (MWF), T1, T2, and pr…
Threshold distribution of equal states for quantitative amplitude fluctuations
Yao Wenpo, Yao Wenli, Wang Jun
Objective. The distribution of equal states (DES) quantifies amplitude fluctuations in biomedical signals. However, under certain conditions, such as a high resolution of data coll…
Delta-alpha cross-frequency coupling for different brain regions
Dushko Lukarski, Spase Petkoski, Peng Ji +1
Neural interactions occur on different levels and scales. It is of particular importance to understand how they are distributed among different neuroanatomical and physiological re…
Exploring Fine-Grained Representation and Recomposition for Cloth-Changing Person Re-Identification
Qizao Wang, Xuelin Qian, Bin Li +2
Cloth-changing person Re-IDentification (Re-ID) is a particularly challenging task, suffering from two limitations of inferior discriminative features and limited training samples.…
ASCON: Anatomy-aware Supervised Contrastive Learning Framework for Low-dose CT Denoising
Zhihao Chen, Qi Gao, Yi Zhang +1
While various deep learning methods have been proposed for low-dose computed tomography (CT) denoising, most of them leverage the normal-dose CT images as the ground-truth to super…