1.4k citations · 6.3k across the 82 of their papers we have counts for
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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…
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…
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…
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…
Adaptive Negative Evidential Deep Learning for Open-set Semi-supervised Learning
Yang Yu, Danruo Deng, Furui Liu +4
Semi-supervised learning (SSL) methods assume that labeled data, unlabeled data and test data are from the same distribution. Open-set semi-supervised learning (Open-set SSL) consi…
Diffusion Model based Semi-supervised Learning on Brain Hemorrhage Images for Efficient Midline Shift Quantification
Shizhan Gong, Cheng Chen, Yuqi Gong +5
Brain midline shift (MLS) is one of the most critical factors to be considered for clinical diagnosis and treatment decision-making for intracranial hemorrhage. Existing computatio…