Neuroimaging

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22 papers in the last four weeks, up 267% on the four weeks before. 0.2% of all new papers.

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Latest papers 166

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BrainRiem: Riemannian Prototype Learning for Source-Free Cross-Site Brain Network Diagnosis
Jun 28, 2026Kunyu Zhang, Tianxiang XuSource-Free Domain Adaptation Functional Connectivity
Zhengzhou University, Zhengzhou 450000, China · Peking University, Beijing 102600, China
Connectivity Estimation using Stochastic Graph Heat Modelling
Jun 27, 2026Stephan Goerttler, Min Wu, Fei HeGraph Structure Learning Neuroimaging
Centre for Computational Science and Mathematical Modelling, Coventry University, Coventry CV1 5FB, UK · Institute for Infocomm Research, A*STAR, Singapore
BREIT: A Framework for Brain Stroke Reconstruction using Multi-Frequency 3D EIT
Jun 27, 2026Djahid Abdelmoumene, Ishak Ayad, Maï K. Nguyen +1Medical Imaging Fourier Neural Operator
ETIS (UMR 8051), CY Cergy Paris University, ENSEA, CNRS, Cergy France · AGM (UMR 8088), CY Cergy Paris University, CNRS, Cergy, France · Paris-Saclay University, CentraleSupélec, Inria, CVN, Gif-sur-Yvette, France
A Neuroimaging Simulation Framework for Developing and Evaluating Causal AI
Jun 27, 2026Eryn Libert-Scott, Emma A. M. Stanley, Vibujithan Vigneshwaran +3Image Generation Causal Discovery
Biomedical Engineering Graduate Program, University of Calgary, Calgary, AB, Canada · Department of Radiology, the Hotchkiss Brain Institute, the Alberta Children’s Hospital Research Institute, and Department of Clinical Neuroscience, all at the University of Calgary, Calgary, Alberta, Canada · Department of Computing, Imperial College London, London, U.K. +1
Physics-Grounded Disentangled Flow Modeling for Brain Disease Progression Trajectory
Jun 26, 2026Jun Wang, Peirong LiuFlow Matching Longitudinal Medical Image Analysis
Department of Electrical and Computer Engineering, Data Science and AI Institute, Johns Hopkins University
Interpretable machine learning predicts Parkinson's disease severity using motion-corrected QSM MRI and multiband multiecho fMRI features
Jun 26, 2026Aixa X. AndradeClinical Outcome Prediction Explainable Medical Image Analysis
Lyda Hill Department of Bioinformatics · Department of Biomedical Engineering · University of Texas Southwestern Medical Center, Dallas, Texas, USA
Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology
Jun 25, 2026Kyriaki-Margarita Bintsi, Sparsh Makharia, Yaël Balbastre +4Synthetic Data Augmentation Synthetic Data Generation
Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States · Krea University, Sri City, Andhra Pradesh, India · Department of Experimental Psychology, University College London, London, United Kingdom +3
Modeling Local, Global, and Cross-Modal Context in Multimodal 3D MRI
Jun 25, 2026Minh Duc Do, Tillmann Rheude, Noel Kronenberg +23D ViTs Brain Age Prediction
1Berlin Institute of Health at Charité - Universitätsmedizin Berlin · 2Health Data Science Unit, Heidelberg University Hospital and BioQuant · 3Intelligent Medicine Institute, Fudan University +1
Heterogeneous Neural Predictivity from Language Models During Naturalistic Comprehension
Jun 25, 2026Xiao JiaNeuroimaging Neural Encoding
School of Artificial Intelligence The Chinese University of Hong Kong, Shenzhen
Beyond Single-Source Cognitive Taskonomy:Multi-Source Task Relations through fMRI Transfer Learning
Jun 24, 2026Junfeng Xia, Wendu Li, Mengjiao Zhang +1Task Transferability Estimation Cross-Domain Transfer Learning
Department of Biomedical Engineering, Southern University of Science and Technology Shenzhen, China
TensorLDM: A Component-Wise Latent Diffusion Model for Volumetric DTI Reconstruction from Sparse DWIs
Jun 24, 2026Junhyeok Lee, Kyu Sung ChoiLatent Diffusion Models Accelerated MRI Reconstruction
Interdisciplinary Program in Cancer Biology, Seoul National University College of Medicine · Department of Radiology, Seoul National University Hospital · Department of Radiology, Seoul National University College of Medicine +1
Native space based pipelines outperform template space based pipeline in subcortical segmentation
Jun 19, 2026Tomás Lima, Daniel Novák, Eduard BakšteinDomain Adaptation Medical Image Segmentation
Department of Cybernetics, Czech Technical University in Prague, Prague, Czech Republic · National Institute of Mental Health, Klecany, Czech Republic
SMART: A Flexible, Interpretable, and Scalable Spatio-temporal Brain Atlas from High-Resolution Imaging Data
Jun 17, 2026John Kalkhof, Boris Gutman, Emile d'Angremont +2Longitudinal Medical Image Analysis Neuroimaging
IIT · Inria Center at University Côte d’Azur Sophia Antipolis, France · Illinois Institute of Technology Chicago, IL, USA +4
A Quantitative Analysis of Multimodal Biomarkers in Alzheimer's Disease
Jun 16, 2026Antonio Scardace, Daniele RavìAlzheimer's Disease Neuroimaging
Department of Mathematics and Computer Science University of Catania Catania, Italy · Department MIFT University of Messina Messina, Italy
BrainWorld: A Structural-Prior-Conditioned Generative Model for Whole-Brain 4D fMRI Dynamics
Jun 16, 2026Junfeng Xia, Wenhao Ye, Junxiang Zhang +3Medical Image Synthesis Neuroimaging
Department of Biomedical Engineering, Southern University of Science and Technology, China · School of Biomedical Engineering, Shenzhen University, China
Feynman Kac Reweighted Schrödinger Bridge Matching for Surface-Based Tau PET Harmonization
Jun 16, 2026Jianwei Zhang, Xinyu Nie, Jiaxin Yue +1Schrödinger Bridges Neuroimaging
Stevens Neuroimaging and Informatics Institute, University of Southern California, Los Angeles, CA 90089 USA · Ming Hsieh Department of Electrical and Computer Engineering of Viterbi School of Engineering, University of Southern California, Los Angeles, CA 90089 USA · Alfred E. Mann Department of Biomedical Engineering of Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
MindAlign: Decoding Inner Speech from fMRI Signals via Multimodal Embedding Alignment under Limited Data
Jun 15, 2026Muxuan Liu, Ichiro Kobayashi, Satoshi NishidaNeural Decoding Neuroimaging
Graduate School of Humanities and Sciences Ochanomizu University · Center for Information and Neural Networks Advanced ICT Research Institute National Institute of Information and Communications Technology
Sex-based Network-Specific Differences in Connectomes: A Krakencoder-Based Analysis
Jun 15, 2026Vibhashree S H, Debanjali Bhattacharya, Vamshi Krishna Kancharla +1Functional Connectivity Neuroimaging
Centre for Brain Research, Indian Institute of Science, Bengaluru 560012, India · Dept. of Artificial Intelligence, Amrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Bengaluru 560035, India
DynFS-MoE: Dynamic Functional-Structural Mixture-of-Experts for Post-Traumatic Epilepsy Diagnosis
Jun 15, 2026Jun-En Ding, Spencer Chen, Henry Noren +6Medical Diagnosis Neuroimaging
Department of Industrial and Systems Engineering, Rutgers University, Piscataway, NJ, USA · Department of Systems Engineering, Stevens Institute of Technology, Hoboken, NJ, USA
Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression
Jun 14, 2026Nguyen Linh Dan LeCausal Effect Estimation Structural Causal Models
Department of Biomedical Engineering The University of Melbourne, Melbourne, Australia
Lesion-DDPM: Lesion-Enhanced 3D Diffusion for MS MRI Synthesis
Jun 13, 2026Weidong Zhang, Yongchan Jung, Shafayat Mowla Anik +5Medical Image Synthesis Diffusion MRI
Northeastern University, Vancouver, BC · Fairleigh Dickinson University, Vancouver, BC · University of Colorado at Colorado Springs, Colorado Springs, CO +2
Learning Sparse Latent Predictive Foundation Model for Multimodal Neuroimaging
Jun 12, 2026Haoxu Huang, Long Chen, Jingyun Chen +8Medical Imaging Foundation Models Joint-Embedding Predictive Architecture
New York University, Center for Data Science, New York, NY, 10001, USA · NYU Grossman School of Medicine, Department of Radiology, New York, NY, 10016, USA · State University of New York at Binghamton, School of Computing, Binghamton, NY 13902, USA +7
iLENS: Interpretable LLM-Guided Mixture-of-Experts for Neuroimaging Survival Analysis
Jun 12, 2026Farica Zhuang, Seong Woo Han, Zixuan Wen +3Mixture of Experts Survival Analysis
University of Pennsylvania · Yale University
Leptomeningeal Collateral Detection on DSA via Vessel-Graph Neural Networks
Jun 12, 2026Junyong Cao, Hakim Baazaoui, Chinmay Prabhakar +5Medical Imaging Graph Neural Networks
University of Zurich, Zurich, Switzerland · University Hospital Zurich, Zurich, Switzerland
Hybrid Classical-Quantum (HCQ) Alzheimer's Classification via Supervised $β$ -VAE and Quantum Kernels
Jun 12, 2026Tia Tiwari, Vamshi Krishna Kancharla, Neelam SinhaVariational Autoencoders Hybrid Quantum-Classical ML
Centre for Brain Research, Indian Institute of Science · Vision and AI Lab (VAL), Indian Institute of Science
Artemis: Anatomy-Resolved inTervention for Eliminating Multimodal NeuroImage confounderS
Jun 10, 2026Siyuan Dai, Yang Du, Kun Zhao +6Graph Neural Networks Multimodal Graph Learning
Department of Electrical and Computer Engineering, University of Pittsburgh, Pittsburgh, PA. · Department of Computer Science, University of Maryland, College Park, MD · Imaging Genetics Center, Mark & Mary Stevens Institute for Neuroimaging & Informatics, Keck School of Medicine, University of Southern California, Los Angeles, CA +2
FlexiBrain: Resolution-Agnostic Voxel-Level Encoding for Native fMRI
Jun 9, 2026Mo Wang, Wenhao Ye, Junfeng Xia +3Medical Imaging Foundation Models fMRI Foundation Models
Southern University of Science and Technology · University of Warwick
DD-INR: Dynamics-Driven Implicit Neural Representation for Accelerated Whole-Brain Functional MRI Reconstruction
Jun 9, 2026Qiaoxin Li, Caini Pan, Pierre-Antoine Comby +2Implicit Neural Representations Accelerated MRI Reconstruction
MIND · MIND, Inria, Palaiseau, France · Neurospin, CEA Paris Saclay, France +3
Poisson Flow of Cortical Folding in Juvenile Myoclonic Epilepsy
Jun 7, 2026Moo K. Chung, Luigi Maccotta, Aaron StruckNeuroimaging
University of Wisconsin, Madison, USA · Washington University, St. Louis, USA
Decoding Naturalistic Emotion Dynamics from the Brain: An LLM-Enhanced Regression Framework
Jun 5, 2026Lemei Zhang, Peng Liu, Hans Dahle Kvadsheim +5Neural Decoding Neuroimaging
Department of Computer Science, NTNU,Trondheim 7491, Norway · Kavli Institute for Systems Neuroscience, NTNU, Trondheim 7491, Norway · Microsoft, Trondheim 7012, Norway

Jun 28, 2026, cs.LGJ/K move · Enter open · S save

BrainRiem: Riemannian Prototype Learning for Source-Free Cross-Site Brain Network Diagnosis

Kunyu Zhang, Tianxiang Xu

Zhengzhou University, Zhengzhou 450000, China · Peking University, Beijing 102600, China

Source-Free Domain Adaptation Functional Connectivity Neuroimaging

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Multi-site functional MRI (fMRI) studies are essential for robust neuropsychiatric diagnosis yet suffer severe domain shifts from scanner heterogeneity, demographics, and site-specific acquisition protocols. Traditional domain adaptation requires concurrent source and target data access, violating clinical privacy regulations. Moreover, functional connectivity matrices lie on the Symmetric Positive Definite (SPD) manifold, where Euclidean operations cause geometric distortions corrupting diagnostic patterns. We propose BrainRiem, a source-free domain adaptation framework learning compact Riemannian brain prototypes via manifold-aware bi-level optimization. It employs the Log-Euclidean Metric to ensure prototypes remain valid SPD matrices, while Dirichlet Energy spectral calibration aligns their frequency characteristics with real brain networks. Only anonymized prototypes are transmitted to target sites, serving as stable anchors for training local models without source data access and reducing leakage under the evaluated attacks. Comprehensive experiments on ABIDE and REST-meta-MDD show BrainRiem consistently outperforms state-of-the-art source-free, traditional, and graph domain adaptation methods across diverse scanners and demographics. Notably, learned prototypes exhibit biologically interpretable connectivity patterns aligning with established neuroscience findings, validating the necessity of Riemannian geometry for brain network analysis.

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