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VQA-Med: Overview of the Medical Visual Question Answering Task at ImageCLEF 2019
2019
Conference and Labs of the Evaluation Forum
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This paper presents an overview of the Medical Visual Question Answering task (VQA-Med) at ImageCLEF 2019. ...
Participating systems were tasked with answering medical questions based on the visual content of radiology images. ...
Acknowledgments This work was supported by the intramural research program at the U.S. National Library of Medicine, National Institutes of Health. We thank Dr. James G. ...
dblp:conf/clef/AbachaHDLDM19
fatcat:gpu5qdvcvzgdnpfwp2is5i7gwa
SSN MLRG at VQA-MED 2021: An Approach for VQA to Solve Abnormality Related Queries using Improved Datasets
2021
Conference and Labs of the Evaluation Forum
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The Visual Question Answering (VQA) in the medical domain attains tremendous advancement in last few years. ...
These four datasets are build by collecting the samples from previous ImageCLEF VQA -MED tasks. ...
The overview of ImageCLEF VQA -MED tasks (2018, 2019 and 2020) are summarized and given in Table 1 . From the results, the observations are: (i). ...
dblp:conf/clef/SitaraS21
fatcat:7j224ar465fj5nyzr3btjdkiiq
Overview of the VQA-Med Task at ImageCLEF 2021: Visual Question Answering and Generation in the Medical Domain
2021
Conference and Labs of the Evaluation Forum
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This paper presents an overview of the fourth edition of the Medical Visual Question Answering (VQA-Med) task at ImageCLEF 2021. ...
VQA-Med 2021 includes a task on Visual Question Answering (VQA), where participants are tasked with answering questions from the visual content of radiology images, and a second task on Visual Question ...
Acknowledgments This work was partially supported by the intramural research program at the U.S. National Library of Medicine, National Institutes of Health. ...
dblp:conf/clef/AbachaSDHM21
fatcat:76fzt5dmcfentdqkhturjsci4y
SYSU-HCP at VQA-Med 2021: A Data-centric Model with Efficient Training Methodology for Medical Visual Question Answering
2021
Conference and Labs of the Evaluation Forum
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This paper describes our contribution to the Visual Question Answering Task in the Medical Domain at ImageCLEF 2021. ...
Our code and model are available at https://github.com/Rodger-Huang/SYSU-HCP-at-ImageCLEF-VQA-Med-2021. ...
To facilitate the lack of the benchmark in the medical VQA, ImageCLEF organizes the 4th edition of the Medical Domain Visual Question Answering Competition named VQA-Med 2021. ...
dblp:conf/clef/GongHCL21
fatcat:ukuxhucuy5d2ncw6xsvsicom4i
Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain
2019
Conference and Labs of the Evaluation Forum
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for the Medical Domain Visual Question Answering challenge hosted by ImageCLEF 2019. ...
The proposed method was ranked 3rd in the Medical Domain Visual Question Answering challenge of Im-ageCLEF 2019. ...
Last, we presented an ensemble method that boosted the performance. Fig. 1 : 1 Fig. 1: Examples of questions and images and their corresponding answers in the ImageCLEF-VQA-Med 2019 challenge. ...
dblp:conf/clef/VuSNL19
fatcat:dm6zj7k2g5hqtd5zcpazxou6te
CGMVQA: A new Classification and Generative Model for Medical Visual Question Answering
2020
IEEE Access
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This model establishes new state-of-the-art results: 0.640 of classification accuracy, 0.659 of word matching and 0.678 of semantic similarity in ImageCLEF 2019 VQA-Med data set. ...
It suggests that the CGMVQA is effective in medical visual question answering and can better assist doctors in clinical analysis and diagnosis. ...
We use the ImageCLEF 2019 VQA-Med data set here. ...
doi:10.1109/access.2020.2980024
fatcat:liiwta2vfrazbnfiiymzdf4d3i
ImageCLEF 2020: Multimedia Retrieval in Lifelogging, Medical, Nature, and Internet Applications
[chapter]
2020
Lecture Notes in Computer Science
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This paper presents an overview of the 2020 ImageCLEF lab that will be organized as part of the Conference and Labs of the Evaluation Forum-CLEF Labs 2020 in Thessaloniki, Greece. ...
ImageCLEF is an ongoing evaluation initiative (run since 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access ...
The medical Visual Question Answering (VQA-Med) task poses a challenging problem that involves both natural language processing and computer vision. ...
doi:10.1007/978-3-030-45442-5_69
fatcat:fpczf3xzrfefbc5rwykvqf4mfm
Medical Visual Question Answering: A Survey
[article]
2022
arXiv
pre-print
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Medical Visual Question Answering~(VQA) is a combination of medical artificial intelligence and popular VQA challenges. ...
Given a medical image and a clinically relevant question in natural language, the medical VQA system is expected to predict a plausible and convincing answer. ...
VQA-Med-2019 VQA-Med-2019 [14] is the second edition of the VQA-Med and was published during the ImageCLEF 2019 challenge. ...
arXiv:2111.10056v2
fatcat:4dihtqmptbgj5lozrv3lfxqv7q
Hierarchical Deep Multi-modal Network for Medical Visual Question Answering
[article]
2020
arXiv
pre-print
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Visual Question Answering in Medical domain (VQA-Med) plays an important role in providing medical assistance to the end-users. ...
proper answers to the queries related to medical images; and thirdly, we study the impact of QS in Medical-VQA by comparing the performance of the proposed model with QS and a model without QS. ...
Recently, the ImageCLEF introduced the challenge of Medical Domain Visual Question Answering, VQA-Med 2018 2 (Ionescu et al., 2018). ...
arXiv:2009.12770v1
fatcat:d2dmtduat5b3bm4ujgyryh474y
OVQA
2022
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval
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Medical visual question answering (Med-VQA) is a challenging problem that aims to take a medical image and a clinical question about the image as input and output a correct answer in natural language. ...
To evaluate the quality of OVQA, we conduct comprehensive experiments on state-of-the-art methods for the Med-VQA task to our dataset. ...
We thank the Affiliated Southeast Hospital of Xiamen University for providing us with electronic medical records. We appreciate Ms. ...
doi:10.1145/3477495.3531724
fatcat:smrinohe6fh4bgeoz4zpmu6j44
A Comparison of Pre-trained Vision-and-Language Models for Multimodal Representation Learning across Medical Images and Reports
[article]
2020
arXiv
pre-print
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Joint image-text embedding extracted from medical images and associated contextual reports is the bedrock for most biomedical vision-and-language (V+L) tasks, including medical visual question answering ...
We also visualize attention maps to illustrate the attention mechanism of V+L models. ...
[20] won the first place in ImageCLEF 2019 VQA-Med [21] competition using the "VGG16+BERT+MFB" model. ...
arXiv:2009.01523v1
fatcat:ktrgckfombbdxmafis2dftdnr4
ViLMedic: a framework for research at the intersection of vision and language in medical AI
2022
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
unpublished
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As of 2022, the library contains a dozen reference implementations replicating the state-of-the-art results for problems that range from medical visual question answering and radiology report generation ...
The library is available at https://github. com/jbdel/vilmedic. ...
Medical Visual Question Answering VQA in the medical domain consists of building systems that answer open-ended questions about medical images ranging from x-rays, MRI to CT scans. ...
doi:10.18653/v1/2022.acl-demo.3
fatcat:lmmxnicjxfg5vgucoby63bjoja
Towards Visual Dialog for Radiology
2020
Proceedings of the 19th SIGBioMed Workshop on Biomedical Language Processing
unpublished
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We show that incorporating medical history of the patient leads to better performance in answering questions as opposed to conventional visual question answering model which looks only at the image. ...
To address this limitation, we introduce a realistic and information-rich task of Visual Dialog in radiology, specific to chest X-ray images. ...
SAN has been successfully adapted for medical VQA tasks such as VQA-RAD (Lau et al., 2018) and VQA-Med task of the ImageCLEF 2018 challenge
2019 Figure 3 : 20193 For example, the pairs {'Other pleural ...
doi:10.18653/v1/2020.bionlp-1.6
fatcat:vcugncpkobb2nayzjgrslhsh44