3 citations · 5 across the 7 of their papers we have counts for
8 papers
Learning Where and What to Lift for Bi-planar X-ray-to-CT Reconstruction
Yifei Wu, Yicheng Wu, Qiang Ma +5
X-ray imaging can be approximately modeled as the projection of an underlying volumetric attenuation field, with each measurement recording the accumulated attenuation along a corr…
Beyond the Global Scores: Fine-Grained Token Grounding as a Robust Detector of LVLM Hallucinations
Tuan Dung Nguyen, Minh Khoi Ho, Qi Chen +8
Large vision-language models (LVLMs) achieve strong performance on visual reasoning tasks but remain highly susceptible to hallucination. Existing detection methods predominantly r…
A High Magnifications Histopathology Image Dataset for Oral Squamous Cell Carcinoma Diagnosis and Prognosis
Jinquan Guan, Junhong Guo, Qi Chen +6
Oral Squamous Cell Carcinoma (OSCC) is a prevalent and aggressive malignancy where deep learning-based computer-aided diagnosis and prognosis can enhance clinical assessments.Howev…
Interpreting Chest X-rays Like a Radiologist: A Benchmark with Clinical Reasoning
Jinquan Guan, Qi Chen, Lizhou Liang +5
Artificial intelligence (AI)-based chest X-ray (CXR) interpretation assistants have demonstrated significant progress and are increasingly being applied in clinical settings. Howev…
A Comprehensive Analysis of Mamba for 3D Volumetric Medical Image Segmentation
Chaohan Wang, Yutong Xie, Qi Chen +2
Mamba, with its selective State Space Models (SSMs), offers a more computationally efficient solution than Transformers for long-range dependency modeling. However, there is still…
A Survey of Medical Vision-and-Language Applications and Their Techniques
Qi Chen, Ruoshan Zhao, Sinuo Wang +9
Medical vision-and-language models (MVLMs) have attracted substantial interest due to their capability to offer a natural language interface for interpreting complex medical data.…
MMCLIP: Cross-modal Attention Masked Modelling for Medical Language-Image Pre-Training
Biao Wu, Yutong Xie, Zeyu Zhang +4
Vision-and-language pretraining (VLP) in the medical field utilizes contrastive learning on image-text pairs to achieve effective transfer across tasks. Yet, current VLP approaches…
PairAug: What Can Augmented Image-Text Pairs Do for Radiology?
Yutong Xie, Qi Chen, Sinuo Wang +7
Current vision-language pre-training (VLP) methodologies predominantly depend on paired image-text datasets, a resource that is challenging to acquire in radiology due to privacy c…