我们利用OmniMedVQA数据集,测试了8个通用多模态大模型:BILP2, MiniGPT-4, InstructBLIP, mPLUGOwl, Otter, LLaVA, LLama adapter v2, 和VPGTrans。以及四个医学多模态模型:Med-Flamingo,RadFM,MedVInT和 LLaVA-Med。实验结果如图5和图6所示,它们分别按5种不同任务类型和12种不同模态体现了各模型的评测结果。
VQA-Med-2019 是一个专注于医学领域的视觉问答数据集,旨在通过图像内容分析来解答问题,无须额外的医学专业知识或领域内推理。它包含四个主要问题类别:影像模态(Modality)、成像平面(Plane)、器官系统(Organ System)以及异常情况(Abnormality)。这些问题按不同的难度级别设计,以适应多样的分类和文本生成方法。数据集共含...
构建全面医学VQA数据集是准确评估多模态大模型医学能力的关键。现有医学VQA数据集在规模与全面性上不足，因此构建一个大规模、全面的数据集至关重要。构建高质量医学VQA数据集面临挑战，需从医学分类数据集出发，结合类别属性与延伸知识生成问题。以肺结核患者胸腔X-Ray影像为例，设计如下QA模版：- Q：该...
An Effective Med-VQA Method Using a Transformer with Weights Fusion of Multiple Fine-Tuned Modelsdoi:10.3390/app13179735VQAmedicalNLPvisiontransformergreedy soupvisual question answeringSWINELECTRAclassificationVisual question answering (VQA) is a task that generates or predicts an answer to a question in...
PathVQA PMC-VQA Med-Halt We thank the authors for their open-sourced code/data and encourage users to cite their works when applicable. If you use this code or data for your research, please cite our work: @article{wu2024hallucination, title={Hallucination Benchmark in Medical Visual Question...
[ICANN 2024] MISS: A Generative Pre-training and Fine-tuning Approach for Med-VQA - TIMMY-CHAN/MISS
Artificial intelligence has made significant strides in medical visual question answering (Med-VQA), yet prevalent studies often interpret images holistically, overlooking the visual regions of interest that may contain crucial information, potentially aligning with a doctor's prior knowledge that can be ...
【VQA文献阅读】VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019,程序员大本营,技术文章内容聚合第一站。
The ImageCLEF 2018 VQA-Med challenge has officially ended and we would like to thank everyone for their participation. The official results are already emailed to corresponding participants. Post-challenge submissions and the leaderboard will remain enabled for a few weeks so you will still be able...
MedPromptX-VQA Introduced by Shaaban et al. in MedPromptX: Grounded Multimodal Prompting for Chest X-ray Diagnosis A new in-context visual question answering dataset encompassing interleaved image and EHR data derived from MIMIC-IV and MIMIC-CXR-JPG databases....