3 citations · 3 across the 4 of their papers we have counts for
4 papers
Task-Specific Knowledge Distillation from the Vision Foundation Model for Enhanced Medical Image Segmentation
Pengchen Liang, Haishan Huang, Bin Pu +7
Large-scale pre-trained models, such as Vision Foundation Models (VFMs), have demonstrated impressive performance across various downstream tasks by transferring generalized knowle…
Rapid Bone Scintigraphy Enhancement via Semantic Prior Distillation from Segment Anything Model
Pengchen Liang, Leijun Shi, Huiping Yao +9
Rapid bone scintigraphy is crucial for diagnosing skeletal disorders and detecting tumor metastases in children, as it shortens scan duration and reduces discomfort. However, accel…
Vision Foundation Models in Medical Image Analysis: Advances and Challenges
Pengchen Liang, Bin Pu, Haishan Huang +4
The rapid development of Vision Foundation Models (VFMs), particularly Vision Transformers (ViT) and Segment Anything Model (SAM), has sparked significant advances in the field of…
Topology-Aware Wavelet Mamba for Airway Structure Segmentation in Postoperative Recurrent Nasopharyngeal Carcinoma CT Scans
Haishan Huang, Pengchen Liang, Naier Lin +6
Nasopharyngeal carcinoma (NPC) patients often undergo radiotherapy and chemotherapy, which can lead to postoperative complications such as limited mouth opening and joint stiffness…