56 citations · 80 across the 12 of their papers we have counts for
12 papers
SAM4Dcap: Training-free Biomechanical Twin System from Monocular Video
Li Wang, HaoYu Wang, Xi Chen +3
Quantitative biomechanical analysis is essential for clinical diagnosis and injury prevention but is often restricted to laboratories due to the high cost of optical motion capture…
Evaluating the Diagnostic Classification Ability of Multimodal Large Language Models: Insights from the Osteoarthritis Initiative
Li Wang, Xi Chen, XiangWen Deng +4
Multimodal large language models (MLLMs) show promising performance on medical visual question answering (VQA) and report generation, but these generation and explanation abilities…
KOM: A Multi-Agent Artificial Intelligence System for Precision Management of Knee Osteoarthritis (KOA)
Weizhi Liu, Xi Chen, Zekun Jiang +11
Knee osteoarthritis (KOA) affects more than 600 million individuals globally and is associated with significant pain, functional impairment, and disability. While personalized mult…
Scaling Tumor Segmentation: Best Lessons from Real and Synthetic Data
Qi Chen, Xinze Zhou, Chen Liu +11
AI for tumor segmentation is limited by the lack of large, voxel-wise annotated datasets, which are hard to create and require medical experts. In our proprietary JHH dataset of 3,…
CT Radiomics-Based Explainable Machine Learning Model for Accurate Differentiation of Malignant and Benign Endometrial Tumors: A Two-Center Study
Tingrui Zhang, Honglin Wu, Zekun Jiang +9
Aimed to develop and validate a CT radiomics-based explainable machine learning model for precise diagnosing malignancy and benignity specifically in endometrial cancer (EC) patien…
Guiding Medical Vision-Language Models with Explicit Visual Prompts: Framework Design and Comprehensive Exploration of Prompt Variations
Kangyu Zhu, Ziyuan Qin, Huahui Yi +4
While mainstream vision-language models (VLMs) have advanced rapidly in understanding image level information, they still lack the ability to focus on specific areas designated by…
EEG-DIF: Early Warning of Epileptic Seizures through Generative Diffusion Model-based Multi-channel EEG Signals Forecasting
Zekun Jiang, Wei Dai, Qu Wei +3
Multi-channel EEG signals are commonly used for the diagnosis and assessment of diseases such as epilepsy. Currently, various EEG diagnostic algorithms based on deep learning have…
NuSegDG: Integration of Heterogeneous Space and Gaussian Kernel for Domain-Generalized Nuclei Segmentation
Zhenye Lou, Qing Xu, Zekun Jiang +6
Domain-generalized nuclei segmentation refers to the generalizability of models to unseen domains based on knowledge learned from source domains and is challenged by various image…
Rough Set improved Therapy-Based Metaverse Assisting System
Jin Cao, Yanhui Jiang, Chang Yu +2
Chronic neck and shoulder pain (CNSP) is a major global public health issue. Traditional treatments like physiotherapy and rehabilitation have drawbacks, including high costs, low…
TV-SAM: Increasing Zero-Shot Segmentation Performance on Multimodal Medical Images Using GPT-4 Generated Descriptive Prompts Without Human Annotation
Zekun Jiang, Dongjie Cheng, Ziyuan Qin +10
This study presents a novel multimodal medical image zero-shot segmentation algorithm named the text-visual-prompt segment anything model (TV-SAM) without any manual annotations. T…
SAM on Medical Images: A Comprehensive Study on Three Prompt Modes
Dongjie Cheng, Ziyuan Qin, Zekun Jiang +3
The Segment Anything Model (SAM) made an eye-catching debut recently and inspired many researchers to explore its potential and limitation in terms of zero-shot generalization capa…
Towards General Purpose Medical AI: Continual Learning Medical Foundation Model
Huahui Yi, Ziyuan Qin, Qicheng Lao +5
Inevitable domain and task discrepancies in real-world scenarios can impair the generalization performance of the pre-trained deep models for medical data. Therefore, we audaciousl…