Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

Quantitative MRI radiomics in the prediction of molecular classifications of breast cancer subtypes in the TCGA/TCIA data set

Using quantitative radiomics, we demonstrate that computer-extracted magnetic resonance (MR) image-based tumor phenotypes can be predictive of the molecular classification of invasive breast cancers. Radiomics analysis was performed on 91 MRIs of biopsy-proven invasive breast cancers from National C...

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Bibliographic Details
Main Authors: Li, Hui, Zhu, Yitan, Burnside, Elizabeth S, Huang, Erich, Drukker, Karen, Hoadley, Katherine A, Fan, Cheng, Conzen, Suzanne D, Zuley, Margarita, Net, Jose M, Sutton, Elizabeth, Whitman, Gary J, Morris, Elizabeth, Perou, Charles M, Ji, Yuan, Giger, Maryellen L
Format: Online
Language:English
Published: Nature Publishing Group 2016
Online Access:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5108580/

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https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5108580/

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