8 citations · 30 across the 34 of their papers we have counts for
15 papers · 1 filter
Unleashing the Potential of Vision-Language Pre-Training for 3D Zero-Shot Lesion Segmentation via Mask-Attribute Alignment
Yankai Jiang, Wenhui Lei, Xiaofan Zhang +1
Recent advancements in medical vision-language pre-training models have driven significant progress in zero-shot disease recognition. However, transferring image-level knowledge to…
MedDiff-FM: A Diffusion-based Foundation Model for Versatile Medical Image Applications
Yongrui Yu, Yannian Gu, Shaoting Zhang +1
Diffusion models have achieved significant success in both natural image and medical image domains, encompassing a wide range of applications. Previous investigations in medical im…
MeNTi: Bridging Medical Calculator and LLM Agent with Nested Tool Calling
Yakun Zhu, Shaohang Wei, Xu Wang +3
Integrating tools into Large Language Models (LLMs) has facilitated the widespread application. Despite this, in specialized downstream task contexts, reliance solely on tools is i…
DeReStainer: H&E to IHC Pathological Image Translation via Decoupled Staining Channels
Linda Wei, Shengyi Hua, Shaoting Zhang +1
Breast cancer is a highly fatal disease among cancers in women, and early detection is crucial for treatment. HER2 status, a valuable diagnostic marker based on Immunohistochemistr…
MedBench: A Comprehensive, Standardized, and Reliable Benchmarking System for Evaluating Chinese Medical Large Language Models
Mianxin Liu, Jinru Ding, Jie Xu +16
Ensuring the general efficacy and goodness for human beings from medical large language models (LLM) before real-world deployment is crucial. However, a widely accepted and accessi…
MedOdyssey: A Medical Domain Benchmark for Long Context Evaluation Up to 200K Tokens
Yongqi Fan, Hongli Sun, Kui Xue +3
Numerous advanced Large Language Models (LLMs) now support context lengths up to 128K, and some extend to 200K. Some benchmarks in the generic domain have also followed up on evalu…
CAT: Coordinating Anatomical-Textual Prompts for Multi-Organ and Tumor Segmentation
Zhongzhen Huang, Yankai Jiang, Rongzhao Zhang +2
Existing promptable segmentation methods in the medical imaging field primarily consider either textual or visual prompts to segment relevant objects, yet they often fall short whe…
Medical Dialogue: A Survey of Categories, Methods, Evaluation and Challenges
Xiaoming Shi, Zeming Liu, Li Du +6
This paper surveys and organizes research works on medical dialog systems, which is an important yet challenging task. Although these systems have been surveyed in the medical comm…
Tool Calling: Enhancing Medication Consultation via Retrieval-Augmented Large Language Models
Zhongzhen Huang, Kui Xue, Yongqi Fan +5
Large-scale language models (LLMs) have achieved remarkable success across various language tasks but suffer from hallucinations and temporal misalignment. To mitigate these shortc…
MedIAnomaly: A comparative study of anomaly detection in medical images
Yu Cai, Weiwen Zhang, Hao Chen +1
Anomaly detection (AD) aims at detecting abnormal samples that deviate from the expected normal patterns. Generally, it can be trained merely on normal data, without a requirement…
Swin-UMamba: Mamba-based UNet with ImageNet-based pretraining
Jiarun Liu, Hao Yang, Hong-Yu Zhou +8
Accurate medical image segmentation demands the integration of multi-scale information, spanning from local features to global dependencies. However, it is challenging for existing…
Modality-Aware and Shift Mixer for Multi-modal Brain Tumor Segmentation
Zhongzhen Huang, Linda Wei, Shaoting Zhang +1
Combining images from multi-modalities is beneficial to explore various information in computer vision, especially in the medical domain. As an essential part of clinical diagnosis…
OpenMEDLab: An Open-source Platform for Multi-modality Foundation Models in Medicine
Xiaosong Wang, Xiaofan Zhang, Guotai Wang +17
The emerging trend of advancing generalist artificial intelligence, such as GPTv4 and Gemini, has reshaped the landscape of research (academia and industry) in machine learning and…
PathoTune: Adapting Visual Foundation Model to Pathological Specialists
Jiaxuan Lu, Fang Yan, Xiaofan Zhang +2
As natural image understanding moves towards the pretrain-finetune era, research in pathology imaging is concurrently evolving. Despite the predominant focus on pretraining patholo…
Evaluating and Enhancing Large Language Models Performance in Domain-specific Medicine: Osteoarthritis Management with DocOA
Xi Chen, MingKe You, Li Wang +7
The efficacy of large language models (LLMs) in domain-specific medicine, particularly for managing complex diseases such as osteoarthritis (OA), remains largely unexplored. This s…