The recognition of breast tumor based on ultrasonic image contour features / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1237-1240, 2006.
Artigo
em Chinês
| WPRIM
| ID: wpr-331440
ABSTRACT
The purpose of this article is to evaluate the role of quantitative margin features in the computer-aided diagnosis of malignant and benign solid breast masses using sonographic imaging. The tumour was seperated by the expert. Three contour features circurity (C), area ratio (A) and length width ratio (LWR) was caculated from the tumour contour. Then back-propagation (BP) neural network with contour features was used to classify tumors into benign and malignant. Results from 119 ultrasonic images have been applied in this experiment. BP neural network yielded the following results:
89.7% and 73.5% respectively. The methods applied in this paper are helpful to raise the correctance of breast cancer diagnosis.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Patologia
/
Processamento de Imagem Assistida por Computador
/
Neoplasias da Mama
/
Diagnóstico por Imagem
/
Ultrassonografia
/
Redes Neurais de Computação
/
Métodos
Tipo de estudo:
Estudo diagnóstico
Limite:
Feminino
/
Humanos
Idioma:
Chinês
Revista:
Journal of Biomedical Engineering
Ano de publicação:
2006
Tipo de documento:
Artigo
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