2 citations · 2 across the 16 of their papers we have counts for
16 papers
Model Merging for Medical LVLMs: A Benchmark and a Winner-Take-All Approach
Lichao Mou, Shilan Zhang, Chunlei Li +7
Large vision-language models (LVLMs) can be adapted to specialized medical imaging tasks via parameter-efficient fine-tuning approaches such as low-rank adaptation (LoRA), leading…
Towards Real-World Ultrasound Understanding: Large Vision-Language Models from Multi-Image Examinations with Long-Form Reports
Bingcong Yan, Chunlei Li, Jingliang Hu +3
Large vision-language models (LVLMs) have achieved strong performance across many medical imaging tasks, yet their application to ultrasound remains limited due to its inherent com…
Learning Domain-Aware Task Prompt Representations for Multi-Domain All-in-One Image Restoration
Guanglu Dong, Chunlei Li, Chao Ren +4
Recently, significant breakthroughs have been made in all-in-one image restoration (AiOIR), which can handle multiple restoration tasks with a single model. However, existing metho…
Dual Distillation for Few-Shot Anomaly Detection
Le Dong, Qinzhong Tan, Chunlei Li +5
Anomaly detection is a critical task in computer vision with profound implications for medical imaging, where identifying pathologies early can directly impact patient outcomes. Wh…
ProPL: Universal Semi-Supervised Ultrasound Image Segmentation via Prompt-Guided Pseudo-Labeling
Yaxiong Chen, Qicong Wang, Chunlei Li +5
Existing approaches for the problem of ultrasound image segmentation, whether supervised or semi-supervised, are typically specialized for specific anatomical structures or tasks,…
High-Order Progressive Trajectory Matching for Medical Image Dataset Distillation
Le Dong, Jinghao Bian, Jingyang Hou +5
Medical image analysis faces significant challenges in data sharing due to privacy regulations and complex institutional protocols. Dataset distillation offers a solution to addres…
Multimodal Large Language Models for Medical Report Generation via Customized Prompt Tuning
Chunlei Li, Jingyang Hou, Yilei Shi +3
Medical report generation from imaging data remains a challenging task in clinical practice. While large language models (LLMs) show great promise in addressing this challenge, the…
Taming Stable Diffusion for Computed Tomography Blind Super-Resolution
Chunlei Li, Yilei Shi, Haoxi Hu +3
High-resolution computed tomography (CT) imaging is essential for medical diagnosis but requires increased radiation exposure, creating a critical trade-off between image quality a…
CausalCLIPSeg: Unlocking CLIP's Potential in Referring Medical Image Segmentation with Causal Intervention
Yaxiong Chen, Minghong Wei, Zixuan Zheng +5
Referring medical image segmentation targets delineating lesions indicated by textual descriptions. Aligning visual and textual cues is challenging due to their distinct data prope…
UniCrossAdapter: Multimodal Adaptation of CLIP for Radiology Report Generation
Yaxiong Chen, Chuang Du, Chunlei Li +5
Automated radiology report generation aims to expedite the tedious and error-prone reporting process for radiologists. While recent works have made progress, learning to align medi…
One-Shot Medical Video Object Segmentation via Temporal Contrastive Memory Networks
Yaxiong Chen, Junjian Hu, Chunlei Li +6
Video object segmentation is crucial for the efficient analysis of complex medical video data, yet it faces significant challenges in data availability and annotation. We introduce…
Ultrasound Image-to-Video Synthesis via Latent Dynamic Diffusion Models
Tingxiu Chen, Yilei Shi, Zixuan Zheng +4
Ultrasound video classification enables automated diagnosis and has emerged as an important research area. However, publicly available ultrasound video datasets remain scarce, hind…
Reducing Annotation Burden: Exploiting Image Knowledge for Few-Shot Medical Video Object Segmentation via Spatiotemporal Consistency Relearning
Zixuan Zheng, Yilei Shi, Chunlei Li +3
Few-shot video object segmentation aims to reduce annotation costs; however, existing methods still require abundant dense frame annotations for training, which are scarce in the m…
Rethinking Cell Counting Methods: Decoupling Counting and Localization
Zixuan Zheng, Yilei Shi, Chunlei Li +3
Cell counting in microscopy images is vital in medicine and biology but extremely tedious and time-consuming to perform manually. While automated methods have advanced in recent ye…
Striving for Simplicity: Simple Yet Effective Prior-Aware Pseudo-Labeling for Semi-Supervised Ultrasound Image Segmentation
Yaxiong Chen, Yujie Wang, Zixuan Zheng +5
Medical ultrasound imaging is ubiquitous, but manual analysis struggles to keep pace. Automated segmentation can help but requires large labeled datasets, which are scarce. Semi-su…
Scale-Aware Contrastive Reverse Distillation for Unsupervised Medical Anomaly Detection
Chunlei Li, Yilei Shi, Jingliang Hu +2
Unsupervised anomaly detection using deep learning has garnered significant research attention due to its broad applicability, particularly in medical imaging where labeled anomalo…