Open AccessIncorporating the clinical and radiomics features of contrast-enhanced mammography to classify breast lesions: a retrospective study
Author(s) -
Simin Wang,
Yuqi Sun,
Ning Mao,
Shaofeng Duan,
Qin Li,
Ruimin Li,
Tingting Jiang,
Zhongyi Wang,
Haizhu Xie,
Yajia Gu
Publication year - 2021
Publication title -
quantitative imaging in medicine and surgery
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.766
H-Index - 21
eISSN - 2223-4306
pISSN - 2223-4292
DOI - 10.21037/qims-21-103
Subject(s) - medicine , radiomics , mammography , logistic regression , mann–whitney u test , radiology , breast imaging , retrospective cohort study , receiver operating characteristic , breast mri , confidence interval , breast cancer , artificial intelligence , computer science , cancer , pathology
Contrast-enhanced mammography (CEM) is a promising breast imaging technique. A limited number of studies have focused on the radiomics analysis of CEM. We intended to explore whether a model constructed with both clinical and radiomics features of CEM can better classify benign and malignant breast lesions.
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