Overview of the ImageCLEF 2022: Multimedia Retrieval in Medical, Social Media and Nature Applications

Abstract

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 ongoing evaluation initiative (first run in 2003) that promotes the evaluation of technologies for annotation, indexing and retrieval of visual data with the aim of providing information access to large collections of images in various usage scenarios and domains. In 2022, the 20th edition of ImageCLEF runs four main tasks: (i) a medical task that groups two previous tasks, i.e., caption analysis and tuberculosis prediction, (ii) a social media aware task on estimating potential real-life effects of online image sharing, (iii) a nature coral task about segmenting and labeling collections of coral reef images, and (iv) a new fusion task addressing the design of late fusion schemes for boosting the performance, with two real-world applications: image search diversification (retrieval) and prediction of visual interestingness (regression). The benchmark campaign received the participation of over 25 groups submitting more than 258 runs.

Christoph M. Friedrich

Principal Investigator

My research interests include Deep Learning, Computer Vision, Radiomics, and Explainable AI.

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.