Multi-feature Extraction and Classification of Breast Tumor in Ultrasound Image / 中国医疗器械杂志
Chinese Journal of Medical Instrumentation
;
(6): 294-301, 2020.
Artigo
em Chinês
| WPRIM
| ID: wpr-828201
ABSTRACT
OBJECTIVE@#Feature extraction of breast tumors is very important in the breast tumor detection (benign and malignant) in ultrasound image. The traditional quantitative description of breast tumors has some shortcomings, such as inaccuracy. A simple and accurate feature extraction method has been studied.@*METHODS@#In this paper, a new method of boundary feature extraction was proposed. Firstly, the shape histogram of ultrasound breast tumors was constructed. Secondly, the relevant boundary feature factors were calculated from a local point of view, including sum of maximum curvature, sum of maximum curvature and peak, sum of maximum curvature and standard deviation. Based on the boundary features, shape features and texture features, the linear support vector machine classifiers for benign and malignant breast tumor recognition was constructed.@*RESULTS@#The accuracy of boundary features in the benign and malignant breast tumors classification was 82.69%. The accuracy of shape features was 73.08%. The accuracy of texture features was 63.46%. The classification accuracy of the three fusion features was 86.54%.@*CONCLUSIONS@#The classification accuracy of boundary features was higher than that of texture features and shape features. The classification method based on multi-features has the highest accuracy and it describes the benign and malignant tumors from different angles. The research results have practical value.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Algoritmos
/
Neoplasias da Mama
/
Diagnóstico por Imagem
/
Ultrassonografia
/
Máquina de Vetores de Suporte
Tipo de estudo:
Estudo diagnóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Chinese Journal of Medical Instrumentation
Ano de publicação:
2020
Tipo de documento:
Artigo
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