14 citations · 31 across the 25 of their papers we have counts for
10 papers · 1 filter
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…
PE-MVCNet: Multi-view and Cross-modal Fusion Network for Pulmonary Embolism Prediction
Zhaoxin Guo, Zhipeng Wang, Ruiquan Ge +6
The early detection of a pulmonary embolism (PE) is critical for enhancing patient survival rates. Both image-based and non-image-based features are of utmost importance in medical…
LKFormer: Large Kernel Transformer for Infrared Image Super-Resolution
Feiwei Qin, Kang Yan, Changmiao Wang +3
Given the broad application of infrared technology across diverse fields, there is an increasing emphasis on investigating super-resolution techniques for infrared images within th…
Accurate Leukocyte Detection Based on Deformable-DETR and Multi-Level Feature Fusion for Aiding Diagnosis of Blood Diseases
Yifei Chen, Chenyan Zhang, Ben Chen +8
In standard hospital blood tests, the traditional process requires doctors to manually isolate leukocytes from microscopic images of patients' blood using microscopes. These isolat…
SCUNet++: Swin-UNet and CNN Bottleneck Hybrid Architecture with Multi-Fusion Dense Skip Connection for Pulmonary Embolism CT Image Segmentation
Yifei Chen, Binfeng Zou, Zhaoxin Guo +5
Pulmonary embolism (PE) is a prevalent lung disease that can lead to right ventricular hypertrophy and failure in severe cases, ranking second in severity only to myocardial infarc…