activity
20222026
most citedMedical SAM 2: Segment medical images as video via Segment Anything Model 2

40 citations · 87 across the 23 of their papers we have counts for

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Showing 2024Show all

6 papers · 1 filter

eess.IV2024

SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation

Jiayuan Zhu, Junde Wu, Cheng Ouyang +2

Medical image segmentation data inherently contain uncertainty. This can stem from both imperfect image quality and variability in labeling preferences on ambiguous pixels, which d…

eess.IV2024

MedUHIP: Towards Human-In-the-Loop Medical Segmentation

Jiayuan Zhu, Junde Wu

Although segmenting natural images has shown impressive performance, these techniques cannot be directly applied to medical image segmentation. Medical image segmentation is partic…

cs.CV2024★ 30 cited

Medical Graph RAG: Towards Safe Medical Large Language Model via Graph Retrieval-Augmented Generation

Junde Wu, Jiayuan Zhu, Yunli Qi +4

We introduce a novel graph-based Retrieval-Augmented Generation (RAG) framework specifically designed for the medical domain, called \textbf{MedGraphRAG}, aimed at enhancing Large…

cs.CV2024★ 40 cited

Medical SAM 2: Segment medical images as video via Segment Anything Model 2

Jiayuan Zhu, Abdullah Hamdi, Yunli Qi +2

Medical image segmentation plays a pivotal role in clinical diagnostics and treatment planning, yet existing models often face challenges in generalization and in handling both 2D…

cs.CV2024★ 2 cited

MGI: Multimodal Contrastive pre-training of Genomic and Medical Imaging

Jiaying Zhou, Mingzhou Jiang, Junde Wu +3

Medicine is inherently a multimodal discipline. Medical images can reflect the pathological changes of cancer and tumors, while the expression of specific genes can influence their…

cs.CV2024

Not just Birds and Cars: Generic, Scalable and Explainable Models for Professional Visual Recognition

Junde Wu, Jiayuan Zhu, Min Xu +1

Some visual recognition tasks are more challenging then the general ones as they require professional categories of images. The previous efforts, like fine-grained vision classific…