14 citations · 31 across the 25 of their papers we have counts for
29 papers
MedGSSR: Generalizable Medical Image Super-Resolution 3D Reconstruction via Hierarchical Feed-forward Gaussian Splatting
Chengkai Wang, Luoyu Hong, Yiting Zhao +7
High-resolution volumetric medical imaging is critical for clinical diagnosis, yet acquisition is often limited by scanner hardware, scan time, and for CT, radiation dose. Medical…
MorVess: Morphology-Aware Pulmonary Vessel Segmentation Network
Fuyou Mao, Yifei Chen, Beining Wu +9
Accurate pulmonary vessel segmentation remains challenging due to the sparse, tortuous, and multi-scale nature of vascular structures, where small branches are easily lost and topo…
GLeVE: Graph-Guided Lesion Grounding with Proposal Verification in 3D CT
Shuo Jiang, Yuhao Hong, Chunbo Jiang +9
Grounding radiology report descriptions to 3D CT volumes is essential for verifiable clinical interpretation, yet remains challenging due to the semantic-spatial gap between free-t…
R2AoP: Reliable and Robust Angle of Progression Estimation from Intrapartum Ultrasound
Yuanhan Wang, Yifei Chen, Beining Wu +7
Accurate estimation of the Angle of Progression (AoP) from intrapartum transperineal ultrasound is critical for objective assessment of labor progression, yet remains highly sensit…
SR3R: Rethinking Super-Resolution 3D Reconstruction With Feed-Forward Gaussian Splatting
Xiang Feng, Xiangbo Wang, Tieshi Zhong +7
3D super-resolution (3DSR) aims to reconstruct high-resolution (HR) 3D scenes from low-resolution (LR) multi-view images. Existing methods rely on dense LR inputs and per-scene opt…
AnyAD: Unified Any-Modality Anomaly Detection in Incomplete Multi-Sequence MRI
Changwei Wu, Yifei Chen, Yuxin Du +7
Reliable anomaly detection in brain MRI remains challenging due to the scarcity of annotated abnormal cases and the frequent absence of key imaging modalities in real clinical work…
A Large Scale Benchmark for Test Time Adaptation Methods in Medical Image Segmentation
Wenjing Yu, Shuo Jiang, Yifei Chen +9
Test time Adaptation is a promising approach for mitigating domain shift in medical image segmentation; however, current evaluations remain limited in terms of modality coverage, t…
MedGEN-Bench: A Contextually Entangled Benchmark for Open-ended Multimodal Medical Generation
Junjie Yang, Yuhao Yan, Gang Wu +12
Medical vision-language models (VLMs) are increasingly expected to support clinical workflows through diagnostic text and relevant medical images. However, current medical visual b…
Multimodal Feature Prototype Learning for Interpretable and Discriminative Cancer Survival Prediction
Shuo Jiang, Zhuwen Chen, Liaoman Xu +6
Survival analysis plays a vital role in making clinical decisions. However, the models currently in use are often difficult to interpret, which reduces their usefulness in clinical…
SmaRT: Style-Modulated Robust Test-Time Adaptation for Cross-Domain Brain Tumor Segmentation in MRI
Yuanhan Wang, Yifei Chen, Shuo Jiang +7
Reliable brain tumor segmentation in MRI is indispensable for treatment planning and outcome monitoring, yet models trained on curated benchmarks often fail under domain shifts ari…
Geodesic Prototype Matching via Diffusion Maps for Interpretable Fine-Grained Recognition
Junhao Jia, Yunyou Liu, Yifei Sun +4
Nonlinear manifolds are pervasive in deep visual features, where Euclidean distances can misrepresent true similarity. This mismatch is particularly detrimental to prototype-based…
No Modality Left Behind: Adapting to Missing Modalities via Knowledge Distillation for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +6
Accurate brain tumor segmentation is essential for preoperative evaluation and personalized treatment. Multi-modal MRI is widely used due to its ability to capture complementary tu…
Brain-HGCN: A Hyperbolic Graph Convolutional Network for Brain Functional Network Analysis
Junhao Jia, Yunyou Liu, Cheng Yang +4
Functional magnetic resonance imaging (fMRI) reveals complex brain functional networks with hierarchical topologies crucial for cognitive processing. Standard Euclidean Graph Neura…
RTGMFF: Enhanced fMRI-based Brain Disorder Diagnosis via ROI-driven Text Generation and Multimodal Feature Fusion
Junhao Jia, Yifei Sun, Yunyou Liu +5
Functional magnetic resonance imaging (fMRI) is a powerful tool for probing brain function, yet reliable clinical diagnosis is hampered by low signal-to-noise ratios, inter-subject…
Bridging the Gap in Missing Modalities: Leveraging Knowledge Distillation and Style Matching for Brain Tumor Segmentation
Shenghao Zhu, Yifei Chen, Weihong Chen +5
Accurate and reliable brain tumor segmentation, particularly when dealing with missing modalities, remains a critical challenge in medical image analysis. Previous studies have not…
Towards Practical Alzheimer's Disease Diagnosis: A Lightweight and Interpretable Spiking Neural Model
Changwei Wu, Yifei Chen, Yuxin Du +7
Early diagnosis of Alzheimer's Disease (AD), particularly at the mild cognitive impairment stage, is essential for timely intervention. However, this process faces significant barr…
The enumeration of plane (3,6)-triangulations and the form of odd perfect numbers
Jan Florek
Let be the family of all -connected plane triangulations with vertices of degree or . The number of non-isomorphic triangulations belonging to $\math…
MMLNB: Multi-Modal Learning for Neuroblastoma Subtyping Classification Assisted with Textual Description Generation
Huangwei Chen, Yifei Chen, Zhenyu Yan +4
Neuroblastoma (NB), a leading cause of childhood cancer mortality, exhibits significant histopathological variability, necessitating precise subtyping for accurate prognosis and tr…
XLSTM-HVED: Cross-Modal Brain Tumor Segmentation and MRI Reconstruction Method Using Vision XLSTM and Heteromodal Variational Encoder-Decoder
Shenghao Zhu, Yifei Chen, Shuo Jiang +8
Neurogliomas are among the most aggressive forms of cancer, presenting considerable challenges in both treatment and monitoring due to their unpredictable biological behavior. Magn…
Toward Robust Early Detection of Alzheimer's Disease via an Integrated Multimodal Learning Approach
Yifei Chen, Shenghao Zhu, Zhaojie Fang +9
Alzheimer's Disease (AD) is a complex neurodegenerative disorder marked by memory loss, executive dysfunction, and personality changes. Early diagnosis is challenging due to subtle…
GFE-Mamba: Mamba-based AD Multi-modal Progression Assessment via Generative Feature Extraction from MCI
Zhaojie Fang, Shenghao Zhu, Yifei Chen +9
Alzheimer's Disease (AD) is a progressive, irreversible neurodegenerative disorder that often originates from Mild Cognitive Impairment (MCI). This progression results in significa…
SCKansformer: Fine-Grained Classification of Bone Marrow Cells via Kansformer Backbone and Hierarchical Attention Mechanisms
Yifei Chen, Zhu Zhu, Shenghao Zhu +11
The incidence and mortality rates of malignant tumors, such as acute leukemia, have risen significantly. Clinically, hospitals rely on cytological examination of peripheral blood a…
Infrared Image Super-Resolution via Lightweight Information Split Network
Shijie Liu, Kang Yan, Feiwei Qin +6
Single image super-resolution (SR) is an established pixel-level vision task aimed at reconstructing a high-resolution image from its degraded low-resolution counterpart. Despite t…
Semi-supervised Medical Image Segmentation Method Based on Cross-pseudo Labeling Leveraging Strong and Weak Data Augmentation Strategies
Yifei Chen, Chenyan Zhang, Yifan Ke +6
Traditional supervised learning methods have historically encountered certain constraints in medical image segmentation due to the challenging collection process, high labeling cos…