Medical Visual Question Answering (MedVQA) presents a significant opportunity to enhance diagnostic accuracy and healthcare delivery by leveraging artificial intelligence to interpret and answer questions based on medical images. In this study, we reframe the problem of MedVQA as a generation task that...
Visual Question Answering (VQA) in the medical domain has attracted more attention from research communities in the last few years due to its various applications. This paper investigates several deep learning approaches in building a medical VQA system based on ImageCLEF's VQA-Med dataset, which ...
论文:Consistency-Preserving Visual Question Answering in Medical Imaging 代码:Code MICCAI 2022 University of Bern, Switzerland 数据集: IDRiD:the Indian Diabetic Retinopathy Image Dataset e-Ophta 贡献:提出了一种新的损失函数和相应的训练过程,允许将问题之间的关系包含到训练过程中。具体地说,我们考虑感知和...
PMC-VQA is a large-scale medical visual question-answering dataset, which contains 227k VQA pairs of 149k images that cover various modalities or diseases. - GitHub - xiaoman-zhang/PMC-VQA: PMC-VQA is a large-scale medical visual question-answering data
Paper tables with annotated results for PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
Visual question answering in medical domain (VQA-Med) exhibits great potential for enhancing confidence in diagnosing diseases and helping patients better understand their medical conditions. One of the challenges in VQA-Med is how to better understand a
To achieve this goal, the first step is to create a visual question answering (VQA) dataset where the AI agent is presented with a pathology image together with a question and is asked to give the correct answer. Our work makes the first attempt to build such a dataset. Different from ...
The code for paper: PeFoM-Med: Parameter Efficient Fine-tuning on Multi-modal Large Language Models for Medical Visual Question Answering - jinlHe/PeFoMed
5. Formulating Instructional Question and Visual Answer from Videos: With the aim of formulating med- ical and health-related questions and localizing their visual answer in the videos, we start with the medical instructional videos annotated in the previous step of the dataset creation. A question...
{Visual Question Answering, Medical dataset, Graph neural network, Multi-modal large vision language model, Large Language Model, Chain of thought}, abstract = {Medical Visual Question Answering (VQA) is an important task in medical multi-modal Large Language Models (LLMs), aiming to answer ...