47 citations · 55 across the 8 of their papers we have counts for
8 papers
PanDent: Toward Comprehensive Tooth-Level Structure-Language Consistency in Dental Radiology
Xiaohan Li, Xinyu Liu, Chang Liu +4
Accurate evaluation of multimodal large language models (MLLMs) in dental panoramic radiography (orthopantomogram, OPG) is limited by the lack of fine-grained, clinically reliable…
Harnessing Lightweight Transformer with Contextual Synergic Enhancement for Efficient 3D Medical Image Segmentation
Xinyu Liu, Zhen Chen, Wuyang Li +2
Transformers have shown remarkable performance in 3D medical image segmentation, but their high computational requirements and need for large amounts of labeled data limit their ap…
MetaScope: Optics-Driven Neural Network for Ultra-Micro Metalens Endoscopy
Wuyang Li, Wentao Pan, Xiaoyuan Liu +6
Miniaturized endoscopy has advanced accurate visual perception within the human body. Prevailing research remains limited to conventional cameras employing convex lenses, where the…
Track Any Anomalous Object: A Granular Video Anomaly Detection Pipeline
Yuzhi Huang, Chenxin Li, Haitao Zhang +9
Video anomaly detection (VAD) is crucial in scenarios such as surveillance and autonomous driving, where timely detection of unexpected activities is essential. Although existing m…
Bridge the Gap Between Visual and Linguistic Comprehension for Generalized Zero-shot Semantic Segmentation
Xiaoqing Guo, Wuyang Li, Yixuan Yuan
Generalized zero-shot semantic segmentation (GZS3) aims to achieve the human-level capability of segmenting not only seen classes but also novel class regions unseen in the trainin…
Polyp-Gen: Realistic and Diverse Polyp Image Generation for Endoscopic Dataset Expansion
Shengyuan Liu, Zhen Chen, Qiushi Yang +4
Automated diagnostic systems (ADS) have shown significant potential in the early detection of polyps during endoscopic examinations, thereby reducing the incidence of colorectal ca…
DiffRect: Latent Diffusion Label Rectification for Semi-supervised Medical Image Segmentation
Xinyu Liu, Wuyang Li, Yixuan Yuan
Semi-supervised medical image segmentation aims to leverage limited annotated data and rich unlabeled data to perform accurate segmentation. However, existing semi-supervised metho…
U-KAN Makes Strong Backbone for Medical Image Segmentation and Generation
Chenxin Li, Xinyu Liu, Wuyang Li +5
U-Net has become a cornerstone in various visual applications such as image segmentation and diffusion probability models. While numerous innovative designs and improvements have b…