4 citations · 5 across the 17 of their papers we have counts for
20 papers
MedVTok: A General-Purpose Medical Visual Tokenizer
Chenglong Ma, Yuanfeng Ji, Junzhi Ning +18
Multimodal medical AI requires a common visual interface for encoding heterogeneous imaging evidence for patient condition modeling. However, existing medical visual tokenizers are…
Latent Ordinal Evidence, Misaligned Outputs: Inference-Time Ordinal Lens Alignment for Multimodal LLMs
Haiming Li, Yingsheng Liu, Jingmin Zhu +5
Multimodal LLMs apply the language model interface to visual inputs, where ordinal regression tasks such as age estimation, image quality assessment, and disease grading require au…
A Neurosymbolic Framework for Interpretable Skeleton-Based Seizure Detection via Concept-Driven Logical Reasoning
Talha Ilyas, Deval Mehta, Zongyuan Ge
Video-based seizure detection is essential for the management of epilepsy patients, offering a non-invasive complement to electroencephalography. While several deep learning approa…
EnTrust: Modeling Inter-Modal Conflict for Trustworthy Multimodal Medical Image Analysis
Dwarikanath Mahapatra, Abhijit Das, Behzad Bozorgtabar +5
Multimodal medical imaging fuses complementary anatomical and functional information, yet modalities frequently disagree in pathologically heterogeneous regions. Current segmentati…
Clinically Aligned Geometry Constraints for Robust IVUS Vessel Boundary Segmentation
Yunshu Chen, Litao Yang, Giuseppe Di Giovanni +9
Intravascular ultrasound (IVUS) lumen and external elastic membrane (EEM) segmentation is important for quantitative coronary plaque burden assessment. Errors in lumen or EEM delin…
DermAgent: A Self-Reflective Agentic System for Dermatological Image Analysis with Multi-Tool Reasoning and Traceable Decision-Making
Yize Liu, Siyuan Yan, Ming Hu +5
Dermatological diagnosis requires integrating fine-grained visual perception with expert clinical knowledge. Although Multimodal Large Language Models (MLLMs) facilitate interactiv…
OPGAgent: An Agent for Auditable Dental Panoramic X-ray Interpretation
Zhaolin Yu, Litao Yang, Ben Babicka +7
Orthopantomograms (OPGs) are the standard panoramic radiograph in dentistry, used for full-arch screening across multiple diagnostic tasks. While Vision Language Models (VLMs) now…
DermoGPT: Open Weights and Open Data for Morphology-Grounded Dermatological Reasoning MLLMs
Jinghan Ru, Siyuan Yan, Yuguo Yin +2
Multimodal Large Language Models (MLLMs) show promise for medical applications, yet progress in dermatology lags due to limited training data, narrow task coverage, and lack of cli…
MAKE: Multi-Aspect Knowledge-Enhanced Vision-Language Pretraining for Zero-shot Dermatological Assessment
Siyuan Yan, Xieji Li, Ming Hu +3
Dermatological diagnosis represents a complex multimodal challenge that requires integrating visual features with specialized clinical knowledge. While vision-language pretraining…
Ophora: A Large-Scale Data-Driven Text-Guided Ophthalmic Surgical Video Generation Model
Wei Li, Ming Hu, Guoan Wang +7
In ophthalmic surgery, developing an AI system capable of interpreting surgical videos and predicting subsequent operations requires numerous ophthalmic surgical videos with high-q…
Derm1M: A Million-scale Vision-Language Dataset Aligned with Clinical Ontology Knowledge for Dermatology
Siyuan Yan, Ming Hu, Yiwen Jiang +5
The emergence of vision-language models has transformed medical AI, enabling unprecedented advances in diagnostic capability and clinical applications. However, progress in dermato…
Neighbor Does Matter: Density-Aware Contrastive Learning for Medical Semi-supervised Segmentation
Feilong Tang, Zhongxing Xu, Ming Hu +6
In medical image analysis, multi-organ semi-supervised segmentation faces challenges such as insufficient labels and low contrast in soft tissues. To address these issues, existing…
OphCLIP: Hierarchical Retrieval-Augmented Learning for Ophthalmic Surgical Video-Language Pretraining
Ming Hu, Kun Yuan, Yaling Shen +17
Surgical practice involves complex visual interpretation, procedural skills, and advanced medical knowledge, making surgical vision-language pretraining (VLP) particularly challeng…
MONICA: Benchmarking on Long-tailed Medical Image Classification
Lie Ju, Siyuan Yan, Yukun Zhou +4
Long-tailed learning is considered to be an extremely challenging problem in data imbalance learning. It aims to train well-generalized models from a large number of images that fo…
OphNet: A Large-Scale Video Benchmark for Ophthalmic Surgical Workflow Understanding
Ming Hu, Peng Xia, Lin Wang +11
Surgical scene perception via videos is critical for advancing robotic surgery, telesurgery, and AI-assisted surgery, particularly in ophthalmology. However, the scarcity of divers…
TP-DRSeg: Improving Diabetic Retinopathy Lesion Segmentation with Explicit Text-Prompts Assisted SAM
Wenxue Li, Xinyu Xiong, Peng Xia +2
Recent advances in large foundation models, such as the Segment Anything Model (SAM), have demonstrated considerable promise across various tasks. Despite their progress, these mod…
Generalizing to Unseen Domains in Diabetic Retinopathy with Disentangled Representations
Peng Xia, Ming Hu, Feilong Tang +6
Diabetic Retinopathy (DR), induced by diabetes, poses a significant risk of visual impairment. Accurate and effective grading of DR aids in the treatment of this condition. Yet exi…
CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models
Peng Xia, Ze Chen, Juanxi Tian +21
Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…
Diffusion Model Driven Test-Time Image Adaptation for Robust Skin Lesion Classification
Ming Hu, Siyuan Yan, Peng Xia +5
Deep learning-based diagnostic systems have demonstrated potential in skin disease diagnosis. However, their performance can easily degrade on test domains due to distribution shif…
Enhancing Vision-Language Models Generalization via Diversity-Driven Novel Feature Synthesis
Siyuan Yan, Cheng Luo, Zhen Yu +1
Vision-language foundation models like CLIP have shown impressive zero-shot generalization, but finetuning on downstream datasets can cause overfitting and loss of its generalizati…