Scholar
Lanfeng Zhong
Google Scholar ID: sOvKS2YAAAAJ
University of Electronic Science and Technology of China & Shanghai AI Lab
Citations & Impact
Citations
116
H-index
5
i10-index
4
Publications
14
Co-authors
0
Publications
Resume (English only)
Academic Achievements
- VLM-CPL: Consensus Pseudo Labels from Vision-Language Models for Annotation-Free Pathological Image Classification, IEEE Transactions on Medical Imaging (2025, IF=9.8).
- UniSAL: Unified Semi-Supervised Active Learning for Histopathological Image Classification, Medical Image Analysis (2025, IF=11.8).
- Semi-supervised pathological image segmentation via cross distillation of multiple attentions and Seg-CAM consistency, Pattern Recognition (2024, IF=7.5).
- HAMIL: High-resolution activation maps and interleaved learning for weakly supervised segmentation of histopathological images, IEEE Transactions on Medical Imaging (2023, IF=10.6).
- Efficient Multi-Organ Segmentation from 3D Abdominal CT Images with Lightweight Network and Knowledge Distillation, IEEE Transactions on Medical Imaging (2023, IF=10.6).
- OpenPath: Open-Set Active Learning for Pathology Image Classification via Pre-trained Vision-Language Models, MICCAI 2025, early accept, 9%.
- Semi-supervised Pathological Image Segmentation via Cross Distillation of Multiple Attentions, MICCAI 2023, early accept, 14%.
- SEMI-CONTRANS: Semi-Supervised Medical Image Segmentation via Multi-Scale Feature Fusion and Cross Teaching of CNN and Transformer, ISBI 2024, Oral.
- MetaSSL: A General Heterogeneous Loss for Semi-Supervised Medical Image Segmentation, IEEE Transactions on Medical Imaging (2025, IF=9.8).
- DGHFA: Dynamic Gradient and Hierarchical Feature Alignment for Robust Distillation of Medical VLMs, MICCAI 2025.
- SUGFW: A SAM-Based Uncertainty-Guided Feature Weighting Framework for Cold Start Active Learning, MICCAI 2025.
- CSAL-3D: Cold-Start Active Learning for 3D Medical Image Segmentation via SSL-Driven Uncertainty-Reinforced Diversity Sampling, MICCAI 2025. Best paper shortlist.
Background
- Research Interests: Medical image analysis. Major: Electronic Engineering.
Co-authors