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 …

The eighth edition of the ImageCLEF medical retrieval task was organized in 2011. A subset
of the open access collection of PubMed Central was used as the database in 2011. This …

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 …

Large amounts of medical images are being produced to help physicians in diagnosis and
treatment planning. These images are then archived in PACS (Picture Archival and …

Wearable computing devices are starting to change the way users interact with computers
and the Internet. Among them, Google Glass includes a small screen located in front of the …

This article presents the participation of the medGIFT groupin ImageCLEFmed 2013. Since
2004, the group has participated in themedical image retrieval tasks of ImageCLEF each …

Retrieval systems can supply similar cases with a proven diagnosis to a new example case
under observation to help clinicians during their work. The ImageCLEFmed evaluation …

For difficult cases clinicians usually use their experience and also the information found in
textbooks to determine a diagnosis. Computer tools can help them supply the relevant …