Automated medical image analysis systems often require large amounts of training data with
high quality labels, which are difficult and time consuming to generate. This paper …

This review paper aims to serve as a comprehensive guide and instructional resource for
researchers seeking to effectively implement language models in medical imaging research …

Résumé The 2023 ImageCLEFmedical GANs task is the first edition of this task, examining
the existing hypothesis that GANs (Generative Adversarial Networks) are generating …

The advent of Large Language Models (LLMs) has sparked considerable interest in the
medical image domain, as they can generalize to multiple tasks and offer outstanding …

Medical report generation demands automatic creation of coherent and precise descriptions
for medical images. However, the scarcity of labelled medical image-report pairs poses …

Purpose: This study focuses on the development of automated text generation from
radiology images, termed diagnostic captioning, to assist medical professionals in reducing …

Medical report generation demands automatic creation of coherent and precise descriptions
for medical images. However, the scarcity of labelled medical image-report pairs poses …

Current image captioning methods based on grid features and segmentation features have
achieved some success. However, existing methods combine the two visual features by …

The progress in large language models (LLMs) brings much excitement and efforts in
medical artificial intelligence, which could transform patient-doctor conversation while …

Medical report generation (MRG) is a challenging yet highly demanding task in the
application of multi-modal artificial intelligence in medicine. Typically, training an MRG …