[The application of artificial intelligence on the classification of benign and malignant breast tumors based on dynamic enhanced MR images].
Zhonghua Yi Xue Za Zhi
; 101(37): 3029-3032, 2021 Oct 12.
Article
em Zh
| MEDLINE
| ID: mdl-34638196
ABSTRACT
This retrospective analysis was conducted on clinical obtained DCE-MR images of 198 patients, age from 21 to 79 years(45.5±13.7). The CBAM-ResNet model was developed to perform the classification automatically at the image-level based on deep learning method using the pathological examination as the reference standard,then the classification result of each individual patient was obtained by ensemble learning. The proposed method can have an accuracy of 82.69% for correctly distinguishing between benign and malignant breast tumors at the slice-level based on CBAM-ResNet model and with a sensitivity of 85.67%.. After the voting mechanism is applied, the classification accuracy can reach up to 88.24% at the patient-level with a sensitivity of 87.50%. Our experimental results demonstrated the proposed approach have a high classification accuracy.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Neoplasias da Mama
/
Inteligência Artificial
Tipo de estudo:
Observational_studies
Limite:
Adult
/
Aged
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Female
/
Humans
/
Middle aged
Idioma:
Zh
Revista:
Zhonghua Yi Xue Za Zhi
Ano de publicação:
2021
Tipo de documento:
Article
País de afiliação:
China