activity
20162025
most citedValidation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge

1.4k citations · 6.3k across the 82 of their papers we have counts for

collaborators

83 papers

cs.CV2025

Medical Large Vision Language Models with Multi-Image Visual Ability

Xikai Yang, Juzheng Miao, Yuchen Yuan +4

Medical large vision-language models (LVLMs) have demonstrated promising performance across various single-image question answering (QA) benchmarks, yet their capability in process…

cs.CV2024

Towards Real-World Adverse Weather Image Restoration: Enhancing Clearness and Semantics with Vision-Language Models

Jiaqi Xu, Mengyang Wu, Xiaowei Hu +3

This paper addresses the limitations of adverse weather image restoration approaches trained on synthetic data when applied to real-world scenarios. We formulate a semi-supervised…

cs.CV2023★ 1 cited

Foundation Model for Endoscopy Video Analysis via Large-scale Self-supervised Pre-train

Zhao Wang, Chang Liu, Shaoting Zhang +1

Foundation models have exhibited remarkable success in various applications, such as disease diagnosis and text report generation. To date, a foundation model for endoscopic video…

cs.CV2023★ 114 cited

3DSAM-adapter: Holistic adaptation of SAM from 2D to 3D for promptable tumor segmentation

Shizhan Gong, Yuan Zhong, Wenao Ma +5

Despite that the segment anything model (SAM) achieved impressive results on general-purpose semantic segmentation with strong generalization ability on daily images, its demonstra…

cs.CV2023

Joint Optimization of Class-Specific Training- and Test-Time Data Augmentation in Segmentation

Zeju Li, Konstantinos Kamnitsas, Qi Dou +2

This paper presents an effective and general data augmentation framework for medical image segmentation. We adopt a computationally efficient and data-efficient gradient-based meta…

cs.CV2023★ 2 cited

Video Dehazing via a Multi-Range Temporal Alignment Network with Physical Prior

Jiaqi Xu, Xiaowei Hu, Lei Zhu +4

Video dehazing aims to recover haze-free frames with high visibility and contrast. This paper presents a novel framework to effectively explore the physical haze priors and aggrega…