Integration of strategies based on relevance feedback into a tool for the retrieval of mammographic images

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4 Citas (Scopus)

Resumen

The incidence of breast cancer varies greatly among countries, but statistics show that every year 720,000 new cases will be diagnosed world-wide. However, a high percentage of these cases can be 100% healed if they are detected in early stages. Because symptoms are not visible as far as advanced stages, it makes the treatments more aggressive and also less efficient. Therefore, it is necessary to develop new strategies to detect the formation in early stages. We have developed a tool based on a Case-Based Reasoning kernel for retrieving mammographie images by content analysis. One of the main difficulties is the introduction of knowledge and abstract concepts from domain into the retrieval process. For this reason, the article proposes integrate the human experts perceptions into it by means of an interaction between human and system using a Relevance Feedback strategy. Furthermore, the strategy uses a Self-Organization Map to cluster the memory and improve the time interaction.

Idioma originalInglés
Título de la publicación alojadaIntelligent Data Engineering and Automated Learning, IDEAL 2006 - 7th International Conference, Proceedings
EditorialSpringer Verlag
Páginas116-124
Número de páginas9
ISBN (versión impresa)3540454853, 9783540454854
DOI
EstadoPublicada - 2006
Evento7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006 - Burgos, Espana
Duración: 20 sept 200623 sept 2006

Serie de la publicación

NombreLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen4224 LNCS
ISSN (versión impresa)0302-9743
ISSN (versión digital)1611-3349

Conferencia

Conferencia7th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2006
País/TerritorioEspana
CiudadBurgos
Período20/09/0623/09/06

Huella

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