72 citations · 303 across the 39 of their papers we have counts for
40 papers
Structural-Functional Brain Connectivity Generation via Multimodal Hypergraph-based Flow Matching
Chyong Yi Poh, Hwa Hui Tew, Junn Yong Loo +4
Structural connectivity (SC) and functional connectivity (FC) provide complementary information on interactions between brain regions and are widely used in neuroimaging studies of…
RelA-Diffusion: Relativistic Adversarial Diffusion for Multi-Tracer PET Synthesis from Multi-Sequence MRI
Minhui Yu, Yongheng Sun, David S. Lalush +3
Multi-tracer positron emission tomography (PET) provides critical insights into diverse neuropathological processes such as tau accumulation, neuroinflammation, and -amyloid dep…
Unpaired Volumetric Harmonization of Brain MRI with Conditional Latent Diffusion
Mengqi Wu, Minhui Yu, Shuaiming Jing +3
Multi-site structural MRI is increasingly used in neuroimaging studies to diversify subject cohorts. However, combining MR images acquired from various sites/centers may introduce…
Simulation-based Inference of Developmental EEG Maturation with the Spectral Graph Model
Danilo Bernardo, Xihe Xie, Parul Verma +8
The spectral content of macroscopic neural activity evolves throughout development, yet how this maturation relates to underlying brain network formation and dynamics remains unkno…
Disentangled Latent Energy-Based Style Translation: An Image-Level Structural MRI Harmonization Framework
Mengqi Wu, Lintao Zhang, Pew-Thian Yap +2
Brain magnetic resonance imaging (MRI) has been extensively employed across clinical and research fields, but often exhibits sensitivity to site effects arising from non-biological…
Reconstruction of Cortical Surfaces with Spherical Topology from Infant Brain MRI via Recurrent Deformation Learning
Xiaoyang Chen, Junjie Zhao, Siyuan Liu +2
Cortical surface reconstruction (CSR) from MRI is key to investigating brain structure and function. While recent deep learning approaches have significantly improved the speed of…
Towards Architecture-Agnostic Untrained Network Priors for Image Reconstruction with Frequency Regularization
Yilin Liu, Yunkui Pang, Jiang Li +2
Untrained networks inspired by deep image priors have shown promising capabilities in recovering high-quality images from noisy or partial measurements without requiring training s…
Leveraging Brain Modularity Prior for Interpretable Representation Learning of fMRI
Qianqian Wang, Wei Wang, Yuqi Fang +5
Resting-state functional magnetic resonance imaging (rs-fMRI) can reflect spontaneous neural activities in brain and is widely used for brain disorder analysis.Previous studies pro…
The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Prior
Yilin Liu, Jiang Li, Yunkui Pang +2
Deep Image Prior (DIP) shows that some network architectures naturally bias towards smooth images and resist noises, a phenomenon known as spectral bias. Image denoising is an imme…
Source-Free Unsupervised Domain Adaptation: A Survey
Yuqi Fang, Pew-Thian Yap, Weili Lin +2
Unsupervised domain adaptation (UDA) via deep learning has attracted appealing attention for tackling domain-shift problems caused by distribution discrepancy across different doma…
Brain Tissue Segmentation Across the Human Lifespan via Supervised Contrastive Learning
Xiaoyang Chen, Jinjian Wu, Wenjiao Lyu +6
Automatic segmentation of brain MR images into white matter (WM), gray matter (GM), and cerebrospinal fluid (CSF) is critical for tissue volumetric analysis and cortical surface re…
Longitudinal Prediction of Postnatal Brain Magnetic Resonance Images via a Metamorphic Generative Adversarial Network
Yunzhi Huang, Sahar Ahmad, Luyi Han +6
Missing scans are inevitable in longitudinal studies due to either subject dropouts or failed scans. In this paper, we propose a deep learning framework to predict missing scans fr…
Localizing the Recurrent Laryngeal Nerve via Ultrasound with a Bayesian Shape Framework
Haoran Dou, Luyi Han, Yushuang He +6
Tumor infiltration of the recurrent laryngeal nerve (RLN) is a contraindication for robotic thyroidectomy and can be difficult to detect via standard laryngoscopy. Ultrasound (US)…
Attention-Guided Autoencoder for Automated Progression Prediction of Subjective Cognitive Decline with Structural MRI
Hao Guan, Ling Yue, Pew-Thian Yap +3
Subjective cognitive decline (SCD) is a preclinical stage of Alzheimer's disease (AD) which occurs even before mild cognitive impairment (MCI). Progressive SCD will convert to MCI…
Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning
Alessa Hering, Lasse Hansen, Tony C. W. Mok +50
Image registration is a fundamental medical image analysis task, and a wide variety of approaches have been proposed. However, only a few studies have comprehensively compared medi…
Dual Shape Guided Segmentation Network for Organs-at-Risk in Head and Neck CT Images
Shuai Wang, Theodore Yanagihara, Bhishamjit Chera +3
The accurate segmentation of organs-at-risk (OARs) in head and neck CT images is a critical step for radiation therapy of head and neck cancer patients. However, manual delineation…
Learning MRI Artifact Removal With Unpaired Data
Siyuan Liu, Kim-Han Thung, Liangqiong Qu +3
Retrospective artifact correction (RAC) improves image quality post acquisition and enhances image usability. Recent machine learning driven techniques for RAC are predominantly ba…
Deformable Registration of Brain MR Images via a Hybrid Loss
Luyi Han, Haoran Dou, Yunzhi Huang +1
Unsupervised learning strategy is widely adopted by the deformable registration models due to the lack of ground truth of deformation fields. These models typically depend on the i…
SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection
Qin Liu, Han Deng, Chunfeng Lian +8
We propose a multi-stage coarse-to-fine CNN-based framework, called SkullEngine, for high-resolution segmentation and large-scale landmark detection through a collaborative, integr…
Learning Multi-Site Harmonization of Magnetic Resonance Images Without Traveling Human Phantoms
Siyuan Liu, Pew-Thian Yap
Harmonization improves data consistency and is central to effective integration of diverse imaging data acquired across multiple sites. Recent deep learning techniques for harmoniz…
A Self-Supervised Deep Framework for Reference Bony Shape Estimation in Orthognathic Surgical Planning
Deqiang Xiao, Hannah Deng, Tianshu Kuang +11
Virtual orthognathic surgical planning involves simulating surgical corrections of jaw deformities on 3D facial bony shape models. Due to the lack of necessary guidance, the planni…
Real-Time Mapping of Tissue Properties for Magnetic Resonance Fingerprinting
Yilin Liu, Yong Chen, Pew-Thian Yap
Magnetic resonance Fingerprinting (MRF) is a relatively new multi-parametric quantitative imaging method that involves a two-step process: (i) reconstructing a series of time frame…
Altered connectedness of the brain chronnectome during the progression of Alzheimer's disease
M. Ghanbari, Z. Zhou, L-M. Hsu +5
Graph theory has been extensively used to investigate brain network topology and its changes in disease cohorts. However, many graph theoretic analysis-based brain network studies…
Navigator-Free Submillimeter Diffusion Imaging using Multishot-encoded Simultaneous Multi-slice (MUSIUM)
Wei-Tang Chang, Khoi Minh Huynh, Pew-Thian Yap +1
The ability to achieve submillimter isotropic resolution diffusion MR imaging (dMRI) is critically important to study fine-scale brain structures, particularly in the cortex. One o…