International audienceObject: Quantitative analysis in MRI is challenging due to variabilities in intensity distributions across patients, acquisitions and scanners and suffers from bias field inhomogeneity. Radiomic studies are impacted by these effects that affect radiomic feature values. This paper describes a dedicated pipeline to increase reproducibility in breast MRI radiomic studies. Materials and Methods: T1, T2, and T1-DCE MR images of two breast phantoms were acquired using two scanners and three dual breast coils. Images were retrospectively corrected for bias field inhomogeneity and further normalised using Z-score or histogram matching. Extracted radiomic features were harmonised between coils by the ComBat method. The whole pi...
Background Radiomic features extracted from breast MRI have potential for diagnostic, prognostic, an...
A multicentre study was undertaken to provide fundamentals for improved standardization and optimize...
Machine learning models based on radiomic features allow us to obtain biomarkers that are capable of...
International audienceObject: Quantitative analysis in MRI is challenging due to variabilities in in...
Radiomics is an emerging field using the extraction of quantitative features from medical images for...
Radiomics is an emerging field using the extraction of quantitative features from medical images for...
Recently, investigators have illustrated the limited reproducibility in radiomics research preventin...
Background Most MRI radiomics studies to date, even multi-centre ones, have used "pure" datasets del...
Radiomics-the high throughput extraction of quantitative features from medical images and their corr...
BACKGROUND: In this study, we sought to investigate if computer-extracted magnetic resonance imaging...
© 2020 American Association of Physicists in Medicine Introduction: This work describes the developm...
Radiomics is the process of converting medical images into minable high-dimensional data to support ...
The purpose of this multicenter retrospective study was to evaluate radiomics analysis coupled with ...
Purpose: Radiomics are quantitative features extracted from medical images. Many radiomic features d...
Purpose: Radiomics are quantitative features extracted from medical images. Many radiomic features d...
Background Radiomic features extracted from breast MRI have potential for diagnostic, prognostic, an...
A multicentre study was undertaken to provide fundamentals for improved standardization and optimize...
Machine learning models based on radiomic features allow us to obtain biomarkers that are capable of...
International audienceObject: Quantitative analysis in MRI is challenging due to variabilities in in...
Radiomics is an emerging field using the extraction of quantitative features from medical images for...
Radiomics is an emerging field using the extraction of quantitative features from medical images for...
Recently, investigators have illustrated the limited reproducibility in radiomics research preventin...
Background Most MRI radiomics studies to date, even multi-centre ones, have used "pure" datasets del...
Radiomics-the high throughput extraction of quantitative features from medical images and their corr...
BACKGROUND: In this study, we sought to investigate if computer-extracted magnetic resonance imaging...
© 2020 American Association of Physicists in Medicine Introduction: This work describes the developm...
Radiomics is the process of converting medical images into minable high-dimensional data to support ...
The purpose of this multicenter retrospective study was to evaluate radiomics analysis coupled with ...
Purpose: Radiomics are quantitative features extracted from medical images. Many radiomic features d...
Purpose: Radiomics are quantitative features extracted from medical images. Many radiomic features d...
Background Radiomic features extracted from breast MRI have potential for diagnostic, prognostic, an...
A multicentre study was undertaken to provide fundamentals for improved standardization and optimize...
Machine learning models based on radiomic features allow us to obtain biomarkers that are capable of...