1 citations · 1 across the 5 of their papers we have counts for
5 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…
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…
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…
Towards Cross-Domain Single Blood Cell Image Classification via Large-Scale LoRA-based Segment Anything Model
Yongcheng Li, Lingcong Cai, Ying Lu +7
Accurate classification of blood cells plays a vital role in hematological analysis as it aids physicians in diagnosing various medical conditions. In this study, we present a nove…