Medical image retrieval by high level semantic features and low level content features of image / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1237-1240, 2009.
Artigo
em Chinês
| WPRIM
| ID: wpr-244653
ABSTRACT
Content-based image retrieval aims at searching the similar images using low level features,and medical image retrieval needs it for the retrieval of similar images. Medical images contain not only a lot of content data, but also a lot of semantic information. This paper presents an approach by combining digital imaging and communications in medicine (DICOM) features and low level features to perform retrieval on medical image databases. At the first step, the semantic information is extracted from DICOM header for the pre-filtering of the images, and then dual-tree complex wavelet transfrom(DT-CWT) features of pre-filtered images and example images are extracted to retrieve similar images. Experimental results show that by combining the high level semantics (DICOM features) and low level content features (texture) the retrieval time is reduced and the performance of medical image retrieval is increased.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Processamento de Imagem Assistida por Computador
/
Interface Usuário-Computador
/
Inteligência Artificial
/
Diagnóstico por Imagem
/
Armazenamento e Recuperação da Informação
/
Sistemas de Informação em Radiologia
/
Integração de Sistemas
/
Métodos
Tipo de estudo:
Estudo diagnóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2009
Tipo de documento:
Artigo
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