The availability of medical imaging data from clinical archives, research literature, and
clinical manuals, coupled with recent advances in computer vision offer the opportunity for …

In 2013, the tenth edition of the medical task of the Image-CLEF benchmark was organized.
For the first time, the ImageCLEFmed workshop takes place in the United States of America …

Rapid advancement in imaging technology generates an enormous amount of
heterogeneous medical data for disease diagnosis and rehabilitation process. Radiologists …

In this paper we propose a complete pipeline for medical image modality classification
focused on the application of discrete Bayesian network classifiers. Modality refers to the …

Much of medical knowledge is stored in the biomedical literature, collected in archives like
PubMed Central that continue to grow rapidly. A significant part of this knowledge is …

In this paper we depict an implemented system for medical image retrieval. Our system
performs retrieval based on both textual and visual content, separately and combined, using …

Motivation Images convey essential information in biomedical publications. As such, there is
a growing interest within the bio-curation and the bio-databases communities, to store …

With the increasing adoption of teledermatology, there is a need to improve the automatic
organization of medical records, being dermatological image modality a key filter in this …

This paper presents a robust method for the classification of medical image types in figures
of the biomedical literature using the fusion of visual and textual information. A deep …

In 2013, the tenth edition of the medical task of the Image-CLEF benchmark was organized.
For the first time, the ImageCLEFmedworkshop takes place in the United States of America …