A radiomics study of textural features using magnetic resonance imaging for classification of breast cancer subtypes

A radiomics study of textural features using magnetic resonance imaging for classification of breast cancer subtypes

Breast cancer is usually screened using mammography and biopsy is used to confirm diagnosis. Recent radiomics approaches suggest predictive associations between images and medical outcome. This study aims to classify breast cancer subtypes using textural features derived from magnetic resonance imag...

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Bibliographic Details
Main Authors: Ng, B.Y (Author), Ninomiya, K. (Author), Rahmat, K. (Author), Ramli, M.T (Author), Tan, L.K (Author), Tang, Z.Y (Author), Wong, J.H.D (Author), Yusoff A.N (Author), Zin H.M (Author)
Format: Article
Language:English
Published: Institute of Physics Publishing, 2020
Subjects:
Breast tissues
Classification (of information)
Clinical diagnosis
Diagnosis
Diseases
Dynamic contrast
Dynamics
Leave-one-out cross-validation (LOOCV)
Logistic regression
Magnetic resonance imaging
Medical imaging
Medical Physics
MRI sequences
Multinomial logistic regression
Principal component analysis
Textural feature
Texture features
Textures
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