Breast Tumor Characterization Using [<sup>18</sup>F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics

Breast Tumor Characterization Using [<sup>18</sup>F]FDG-PET/CT Imaging Combined with Data Preprocessing and Radiomics

<i>Background</i>: This study investigated the performance of ensemble learning holomic models for the detection of breast cancer, receptor status, proliferation rate, and molecular subtypes from [<sup>18</sup>F]FDG-PET/CT images with and without incorporating data pre-proces...

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Bibliographic Details
Main Authors: Denis Krajnc, Laszlo Papp, Thomas S. Nakuz, Heinrich F. Magometschnigg, Marko Grahovac, Clemens P. Spielvogel, Boglarka Ecsedi, Zsuzsanna Bago-Horvath, Alexander Haug, Georgios Karanikas, Thomas Beyer, Marcus Hacker, Thomas H. Helbich, Katja Pinker
Format: Article
Language:English
Published: MDPI AG 2021-03-01
Series:Cancers
Subjects:
breast cancer
radiomics
machine learning
PET/CT
data pre-processing
triple negative
Online Access:https://www.mdpi.com/2072-6694/13/6/1249

Internet

https://www.mdpi.com/2072-6694/13/6/1249

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