Overview of the ImageCLEF 2024: Multimedia Retrieval in Medical Applications

会议论文
发表日期：

2024年

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Bogdan Ionescu,
Henning Müller,
Ana-Maria Drăgulinescu,
Johannes Rückert,
Asma Ben Abacha,
Alba García Seco de Herrera,
Louise Bloch,
Raphael Brüngel,
Ahmad Idrissi-Yaghir,
Henning Schäfer,
Cynthia Sabrina Schmidt,
Tabea M. G. Pakull,
Hendrik Damm,
Benjamin Bracke,
Christoph M. Friedrich,
Alexandra-Georgiana Andrei,
Yuri Prokopchuk,
Dzmitry Karpenka,
Ahmedkhan Radzhabov,
Vassili Kovalev,
Cécile Macaire,
Didier Schwab,
Benjamin Lecouteux,
Emmanuelle Esperança-Rodier,
Wen-Wai Yim,
Yujuan Fu,
Zhaoyi Sun,
Meliha Yetisgen,
Fei Xia,
Steven A. Hicks,
Michael A. Riegler,
Vajira Thambawita,
Andrea Storås,
Pål Halvorsen,
Maximilian Heinrich,
Johannes Kiesel,
Martin Potthast,
Benno Stein

摘要

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.