2 citations · 3 across the 9 of their papers we have counts for
9 papers
Low-Contrast-Enhanced Contrastive Learning for Semi-Supervised Endoscopic Image Segmentation
Lingcong Cai, Yun Li, Xiaomao Fan +3
The segmentation of endoscopic images plays a vital role in computer-aided diagnosis and treatment. The advancements in deep learning have led to the employment of numerous models…
ITCFN: Incomplete Triple-Modal Co-Attention Fusion Network for Mild Cognitive Impairment Conversion Prediction
Xiangyang Hu, Xiangyu Shen, Yifei Sun +8
Alzheimer's disease (AD) is a common neurodegenerative disease among the elderly. Early prediction and timely intervention of its prodromal stage, mild cognitive impairment (MCI),…
VisionLLM-based Multimodal Fusion Network for Glottic Carcinoma Early Detection
Zhaohui Jin, Yi Shuai, Yongcheng Li +4
The early detection of glottic carcinoma is critical for improving patient outcomes, as it enables timely intervention, preserves vocal function, and significantly reduces the risk…
Stain-aware Domain Alignment for Imbalance Blood Cell Classification
Yongcheng Li, Lingcong Cai, Ying Lu +6
Blood cell identification is critical for hematological analysis as it aids physicians in diagnosing various blood-related diseases. In real-world scenarios, blood cell image datas…
SAM-FNet: SAM-Guided Fusion Network for Laryngo-Pharyngeal Tumor Detection
Jia Wei, Yun Li, Meiyu Qiu +3
Laryngo-pharyngeal cancer (LPC) is a highly fatal malignant disease affecting the head and neck region. Previous studies on endoscopic tumor detection, particularly those leveragin…
Domain-invariant Representation Learning via Segment Anything Model for Blood Cell Classification
Yongcheng Li, Lingcong Cai, Ying Lu +8
Accurate classification of blood cells is of vital significance in the diagnosis of hematological disorders. However, in real-world scenarios, domain shifts caused by the variabili…