Abstract
This paper presents an overview of the ImageCLEF 2024 lab, organized as part of the Conference and Labs of the Evaluation Forum – CLEF Labs 2024. ImageCLEF, an ongoing evaluation event since 2003, encourages the evaluation of technologies for annotation, indexing and retrieval of multimodal data. The goal is to provide information access to large collections of data across various usage scenarios and domains. In 2024, the 22st edition of ImageCLEF runs three main tasks: (i) a medical task, continuing the caption analysis, Visual Question Answering for colonoscopy images alongside GANs for medical images, and medical dialogue summarization; (ii) a novel task related to image retrieval/generation for arguments for visual communication, aimed at augmenting the effectiveness of arguments; and (iii)ToPicto, a new task focused on translating natural language, whether spoken or textual, into a sequence of pictograms. The benchmarking capaign was a real success and received the participation of over 35 groups submitting more than 220 runs.
Louise Bloch
Associated Researcher
My research interests include interpretable machine learning, mutlimodal deep learning, and medical image processing.
Raphael Brüngel
Associated Researcher
My research interests include artificial intelligence, computational linguistics, and information retrieval.
Ahmad Idrissi-Yaghir
Researcher in the first cohort
My research interests include Deep Learning, Natural Language Processing, and Information Retrieval.
Henning Schäfer
Researcher in the first cohort
My research interests include Deep Learning, Computer Vision, Radiomics, and Explainable AI.
Hendrik Damm
Researcher in the second cohort
My research interests include Deep Learning, Natural Language Processing, and Information Retrieval.
Benjamin Bracke
Associated Researcher
My research interests include Medical Terminology, Clinical Pathways, and Medical Informatics.