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 …

A common approach to medical image analysis on volumetric data uses deep 2D
convolutional neural networks (CNNs). This is largely attributed to the challenges imposed …

This paper presents an overview of the Medical Visual Question Answering (VQA-Med) task
at ImageCLEF 2020. This third edition of VQA-Med included two tasks:(i) Visual Question …

This paper presents an overview of the ImageCLEF 2022 lab that was organized as part of
the Conference and Labs of the Evaluation Forum–CLEF Labs 2022. ImageCLEF is an …

This paper presents an overview of the ImageCLEF 2021 lab that was organized as part of
the Conference and Labs of the Evaluation Forum–CLEF Labs 2021. ImageCLEF is an …

Deep learning methods have proven extremely effective at performing a variety of medical
image analysis tasks. With their potential use in clinical routine, their lack of transparency …

This paper describes our method for the Medical Domain Visual Question Answering (VQA-
Med) Task of ImageCLEF 2019. The aim is to build a model that is able to answer questions …

In this paper, we present PMData: a dataset that combines traditional lifelogging data with
sports-activity data. Our dataset enables the development of novel data analysis and …

Given a query composed of a reference image and a relative caption, the Composed Image
Retrieval goal is to retrieve images visually similar to the reference one that integrates the …

Building on the recent advances in multimodal zero-shot representation learning, in this
paper we explore the use of features obtained from the recent CLIP model to perform …