Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions

Radiomic and Artificial Intelligence Analysis with Textural Metrics Extracted by Contrast-Enhanced Mammography and Dynamic Contrast Magnetic Resonance Imaging to Detect Breast Malignant Lesions

<b>Purpose</b>:The purpose of this study was to discriminate between benign and malignant breast lesions through several classifiers using, as predictors, radiomic metrics extracted from CEM and DCE-MRI images. In order to optimize the analysis, balancing and feature selection procedures...

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Bibliographic Details
Main Authors: Roberta Fusco, Elio Di Bernardo, Adele Piccirillo, Maria Rosaria Rubulotta, Teresa Petrosino, Maria Luisa Barretta, Mauro Mattace Raso, Paolo Vallone, Concetta Raiano, Raimondo Di Giacomo, Claudio Siani, Franca Avino, Giosuè Scognamiglio, Maurizio Di Bonito, Vincenza Granata, Antonella Petrillo
Format: Article
Language:English
Published: MDPI AG 2022-03-01
Series:Current Oncology
Subjects:
contrast-enhanced mammography
magnetic resonance imaging
image enhancement
contrast media
radiomics
artificial intelligence
Online Access:https://www.mdpi.com/1718-7729/29/3/159

Internet

https://www.mdpi.com/1718-7729/29/3/159

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