Rocov2: Radiology objects in context version 2, an updated multimodal image dataset
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 …
high quality labels, which are difficult and time consuming to generate. This paper …
Overview of the ImageCLEF 2024: Multimedia retrieval in medical applications
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 …
Conference and Labs of the Evaluation Forum–CLEF Labs 2024. ImageCLEF, an ongoing …
Overview of ImageCLEFmedical 2023–caption prediction and concept detection
J Rückert, A Ben Abacha… - Working Notes of the …, 2023 - arodes.hes-so.ch
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 existing hypothesis that GANs (Generative Adversarial Networks) are generating …
[PDF][PDF] Overview of the MEDIQA-Sum Task at ImageCLEF 2023: Summarization and Classification of Doctor-Patient Conversations.
This paper presents the overview of the MEDIQA-Sum task at ImageCLEF 2023. MEDIQA-
Sum 2023 includes three subtasks, in which a doctor-patient dialogue source is given, and …
Sum 2023 includes three subtasks, in which a doctor-patient dialogue source is given, and …
Overview of ImageCLEFmedical GANs 2023 Task: identifying training data “fingerprints” in synthetic biomedical images generated by GANs for medical image security
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 existing hypothesis that GANs (Generative Adversarial Networks) are generating …
Customizing general-purpose foundation models for medical report generation
Medical caption prediction which can be regarded as a task of medical report generation
(MRG), requires the automatic generation of coherent and accurate captions for the given …
(MRG), requires the automatic generation of coherent and accurate captions for the given …
[PDF][PDF] Overview of ImageCLEFmedical 2023-Medical Visual Question Answering for Gastrointestinal Tract.
This paper provides an overview of the Medical Visual Question Answering for
Gastrointestinal Tract (MedVQA-GI) challenge held at ImageCLEF 2023, a new challenge …
Gastrointestinal Tract (MedVQA-GI) challenge held at ImageCLEF 2023, a new challenge …
[PDF][PDF] AUEB NLP Group at ImageCLEFmedical Caption 2023.
This article describes the methods that the AUEB NLP Group experimented with during its
participation in the 7th edition of the ImageCLEFmedical Caption sub-tasks, namely Concept …
participation in the 7th edition of the ImageCLEFmedical Caption sub-tasks, namely Concept …
Uit-saviors at medvqa-gi 2023: Improving multimodal learning with image enhancement for gastrointestinal visual question answering
TM Thai, AT Vo, HK Tieu, LNP Bui… - arxiv preprint arxiv …, 2023 - arxiv.org
In recent years, artificial intelligence has played an important role in medicine and disease
diagnosis, with many applications to be mentioned, one of which is Medical Visual Question …
diagnosis, with many applications to be mentioned, one of which is Medical Visual Question …
[PDF][PDF] Transferring Pre-Trained Large Language-Image Model for Medical Image Captioning.
W Zhou, Z Ye, Y Yang, S Wang, H Huang… - CLEF (Working …, 2023 - ceur-ws.org
This paper introduces the work conducted by the team" closeAI2023" in the
ImageCLEFmedical Caption 2023 Image Caption sub-task. Medical image captioning poses …
ImageCLEFmedical Caption 2023 Image Caption sub-task. Medical image captioning poses …