6 papers
CLIP in Medical Imaging: A Survey
Zihao Zhao, Yuxiao Liu, Han Wu +8
Contrastive Language-Image Pre-training (CLIP), a simple yet effective pre-training paradigm, successfully introduces text supervision to vision models. It has shown promising resu…
MUC: Mixture of Uncalibrated Cameras for Robust 3D Human Body Reconstruction
Yitao Zhu, Sheng Wang, Mengjie Xu +5
Multiple cameras can provide comprehensive multi-view video coverage of a person. Fusing this multi-view data is crucial for tasks like behavioral analysis, although it traditional…
MeLo: Low-rank Adaptation is Better than Fine-tuning for Medical Image Diagnosis
Yitao Zhu, Zhenrong Shen, Zihao Zhao +5
The common practice in developing computer-aided diagnosis (CAD) models based on transformer architectures usually involves fine-tuning from ImageNet pre-trained weights. However,…
Inter-slice Super-resolution of Magnetic Resonance Images by Pre-training and Self-supervised Fine-tuning
Xin Wang, Zhiyun Song, Yitao Zhu +4
In clinical practice, 2D magnetic resonance (MR) sequences are widely adopted. While individual 2D slices can be stacked to form a 3D volume, the relatively large slice spacing can…
Gaze-DETR: Using Expert Gaze to Reduce False Positives in Vulvovaginal Candidiasis Screening
Yan Kong, Sheng Wang, Jiangdong Cai +5
Accurate detection of vulvovaginal candidiasis is critical for women's health, yet its sparse distribution and visually ambiguous characteristics pose significant challenges for ac…
ChatCAD+: Towards a Universal and Reliable Interactive CAD using LLMs
Zihao Zhao, Sheng Wang, Jinchen Gu +6
The integration of Computer-Aided Diagnosis (CAD) with Large Language Models (LLMs) presents a promising frontier in clinical applications, notably in automating diagnostic process…