We establish a scalable pipeline to construct a large-scale medical visual question-answering dataset, named PMC-VQA, which contains 227k VQA pairs of 149k images that cover various modalities or diseases. We train the proposed model on PMC-VQA and then fine-tune it on multiple public bench...
{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 ...
investigate how the large body of publicly available images from the biomedical domain can be used to generate a new medical visual question-answering dataset. Along with the resulting benchmark dataset, the authors propose a novel visual-language model and compare its performance against existing ...
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
gave a detailed description of the current situation of medical visual question answering. there are many vqa datasets widely used in general fields, such as coco-qa [ 36 ], vqa-dataset [ 6 ], fm-iqa [ 37 ], visual genome [ 38 ], visual7w [ 39 ], and clevr [ 40 ]. early vqa...
Paper tables with annotated results for PMC-VQA: Visual Instruction Tuning for Medical Visual Question Answering
The implementation of Medical Visual Question Answering via Conditional Reasoning [ACM MM 2020] We evaluate our proposal on VQA-RAD dataset. Conditional Reasoning Framework We propose QCR [Question-Conditioned Reasoning Module] and TCR [Type-Conditioned Reasoning] modules, which guide the importance sele...
Visual Question Answering (VQA) Datasets Edit ShareGPT4V VQA-RAD PathVQA PMC-VQA PMC-OA Results from the Paper Edit Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers. Methods...
Image and question matching is essential in Medical Visual Question Answering (MVQA) in order to accurately assess the visual-semantic correspondence between an image and a question. However, the recent state-of-the-art methods focus solely on the contrastive learning between an entire image and ...
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...