Overview of the 2005 cross-language image retrieval track (ImageCLEF)

The purpose of this paper is to outline efforts from the 2005 CLEF crosslanguage image retrieval campaign (ImageCLEF). The aim of this CLEF track is to explore the use of both text and content-based retrieval methods for cross-language image retrieval. Four tasks were offered in the ImageCLEF track: a ad-hoc retrieval from an historic photographic collection, ad-hoc retrieval from a medical collection, an automatic image annotation task, and a user-centered (interactive) evaluation task that is explained in the iCLEF summary. 24 research groups from a variety of backgrounds and nationalities (14 countries) participated in ImageCLEF. In this paper we describe the ImageCLEF tasks, submissions from participating groups and summarise the main fndings

Uma metodologia eficiente para recuperação de exames médicos DICOM por similaridade de caracteristicas visuais

Dissertação (Mestrado) - Universidade Federal de Santa Catarina, Centro Tecnológico. Programa de Pós-Graduação em Ciência da Computaçao.À medida que se iniciou o processo de popularização de exames médicos em formato digital, surgiu à necessidade de se desenvolver técnicas capazes de facilitar o processo de tomada de decisão médica. Nesse contexto, técnicas de Recuperação de Imagens Médicas Baseada no Conteúdo - Content-Based Medical Image Retrieval (CBMIR) [MULLER, 2004a] têm sido empregadas

Use Case Oriented Medical Visual Information Retrieval & System Evaluation

Large amounts of medical visual data are produced daily in hospitals, while new imaging techniques continue to emerge. In addition, many images are made available continuously via publications in the scientific literature and can also be valuable for clinical routine, research and education. Information retrieval systems are useful tools to provide access to the biomedical literature and fulfil the information needs of medical professionals. The tools developed in this thesis can potentially help clinicians make decisions about difficult diagnoses via a case-based retrieval system based on a use case associated with a specific evaluation task. This system retrieves articles from the biomedical literature when querying with a case description and attached images. This thesis proposes a multimodal approach for medical case-based retrieval with focus on the integration of visual information connected to text. Furthermore, the ImageCLEFmed evaluation campaign was organised during this thesis promoting medical retrieval system evaluation